Google Patent | Facilitating user-proficiency in using radar gestures to interact with an electronic device

Patent: Facilitating user-proficiency in using radar gestures to interact with an electronic device

Drawings: Click to check drawins

Publication Number: 20210103337

Publication Date: 20210408

Applicant: Google

Assignee: Google Llc

Abstract

This document describes techniques that enable facilitating user-proficiency in using radar gestures to interact with an electronic device. Using the described techniques, an electronic device can employ a radar system to detect and determine radar-based touch-independent gestures (radar gestures) that are made by the user to interact with the electronic device and applications running on the electronic device. For the radar gestures to be used to control or interact with the electronic device, the user must properly perform the radar gestures. The described techniques therefore also provide a game or tutorial environment that allows the user to learn and practice radar gestures in a natural way. The game or tutorial environments also provide visual gaming elements that give the user feedback when radar gestures are properly made and when the radar gestures are not properly made, which makes the learning and practicing a pleasant and enjoyable experience for the user.

Claims

  1. A method performed by a radar-gesture-enabled electronic device for facilitating user proficiency in using gestures received using radar, the facilitating through visual game-play, the method comprising: presenting a first visual gaming element on a display of the radar-gesture-enabled electronic device; receiving first radar data corresponding to a first movement of a user in a radar field provided by a radar system, the radar system included or associated with the radar-gesture-enabled electronic device; determining, based on the first radar data, whether the first movement of the user in the radar field comprises a first radar gesture; and in response to determining that the first movement of the user in the radar field comprises the first radar gesture, presenting a successful visual animation of the first visual gaming element, the successful visual animation of the first visual gaming element indicating a successful advance of the visual game-play; or in response to determining that the first movement of the user in the radar field does not comprise the first radar gesture, presenting an unsuccessful visual animation of the first visual gaming element, the unsuccessful visual animation of the first visual element indicating a failure to advance the visual game-play.

  2. The method of claim 1, further comprising: in response to the determining that the first movement of the user in the radar field does not comprise the first radar gesture, receiving second radar data corresponding to a second movement of the user in the radar field; determining, based on the second radar data, that the second movement of the user in the radar field comprises the first radar gesture; and in response to determining that the second movement of the user in the radar field comprises the first radar gesture, presenting the successful visual animation of the first visual gaming element.

  3. The method of claim 2, wherein the determining, based on the second radar data, whether the second movement of the user in the radar field comprises the first radar gesture further comprises: using the second radar data to detect values of a set of parameters that are associated with the second movement of the user in the radar field; comparing the detected values of the set of parameters to benchmark values for the set of parameters, the benchmark values corresponding to the first radar gesture.

  4. The method of claim 2, further comprising: in response to determining that the first movement or second movement of the user in the radar field comprises the first radar gesture, presenting a second visual gaming element; receiving third radar data corresponding to a third movement of the user in the radar field, the third radar data received after the first radar data and the second radar data; determining, based on the third radar data, that the third movement of the user in the radar field comprises a second radar gesture; and in response to determining that the third movement of the user in the radar field comprises the second radar gesture, presenting a successful visual animation of the second visual gaming element, the successful visual animation of the second visual gaming element indicating another successful advance of the visual game-play.

  5. The method of claim 4, wherein the determining, based on the third radar data, whether the third movement of the user in the radar field comprises the second radar gesture further comprises: using the third radar data to detect values of a set of parameters that are associated with the third movement of the user in the radar field; comparing the detected values of the set of parameters to benchmark values for the set of parameters, the benchmark values corresponding to the second radar gesture.

  6. The method of claim 4, wherein a field of view within which the first radar gesture or the second radar gesture is determined includes a volumes within approximately one meter of the radar-gesture-enabled electronic device and within angles of greater than approximately ten degrees measured from the plane of a display of the radar-gesture-enabled electronic device.

  7. The method of claim 4, further comprising: generating, with a machine-learned model, adjusted benchmark values associated with the first radar gesture or the second radar gesture; receiving fourth radar data corresponding to a fourth movement of the user in the radar field; using the fourth radar data to detect values of a set of parameters that are associated with the fourth movement of the user in the radar field; comparing the detected values of the set of parameters to the adjusted benchmark values; determining, based on the comparison, that the fourth movement of the user in the radar field comprises the first or second radar gesture, and wherein the fourth movement of the user in the radar field is not the first or second radar gesture based on a comparison of the values of the set of parameters to default benchmark values.

  8. The method of claim 1, wherein the determining, based on the first radar data, whether the first movement of the user in the radar field comprises the first radar gesture further comprises: using the first radar data to detect values of a first set of parameters that are associated with the first movement of the user in the radar field; comparing the detected values of the first set of parameters to first benchmark values for the first the set of parameters, the first benchmark values corresponding to the first radar gesture.

  9. The method of claim 1, wherein the first visual gaming element is presented without textual instructions or non-textual instructions associated with how to perform the first radar gesture.

  10. The method of claim 1, wherein the first visual gaming element is presented with a supplementary instruction that describes how to perform the first radar gesture.

  11. A radar-gesture-enabled electronic device, comprising: a computer processor; a radar system, implemented at least partially in hardware, configured to: provide a radar field; sense reflections from a user in the radar field; analyze the reflections from the user in the radar field; and provide, based on the analysis of the reflections, radar data; and a computer-readable media having instructions stored thereon that, responsive to execution by the computer processor, implement a gesture-training module configured to: present, in context of visual game-play, a first visual gaming element on a display of the radar-gesture-enabled electronic device; receive a first subset of the radar data corresponding to a first movement of the user in the radar field; determining, based on the first subset of the radar data, whether the first movement of the user in the radar field comprises a first radar gesture; in response to a determination that the first movement of the user in the radar field comprises the first radar gesture, present a successful visual animation of the first visual gaming element, the successful visual animation of the first visual gaming element indicating a successful advance of the visual game-play; or in response to a determination that the first movement of the user in the radar field does not comprise the first radar gesture, present an unsuccessful visual animation of the first visual gaming element, the unsuccessful visual animation of the first visual element indicating a failure to advance the visual game-play.

  12. The radar-gesture-enabled electronic device of claim 11, wherein the gesture-training module is further configured to: in response to the determination that the first movement of the user in the radar field does not comprise the first radar gesture, receive a second subset of the radar data corresponding to a second movement of the user in the radar field; determine, based on the second subset of the radar data, that the second movement of the user in the radar field comprises the first radar gesture; and in response to the determination that the second movement of the user in the radar field comprises the first radar gesture, present the successful visual animation of the first visual gaming element.

  13. The radar-gesture-enabled electronic device of claim 12, wherein the determination, based on the second subset of the radar data, that the second movement of the user in the radar field comprises the first radar gesture further comprises: using the second radar data to detect values of a set of parameters that are associated with the second movement of the user in the radar field; comparing the detected values of the set of parameters to benchmark values for the set of parameters, the benchmark values corresponding to the first radar gesture.

  14. The radar-gesture-enabled electronic device of claim 12, wherein the gesture-training module is further configured to: in response to the determination that the first movement or the second movement of the user in the radar field comprises the first radar gesture, present a second visual gaming element; receive a third subset of the radar data corresponding to a third movement of the user in the radar field, the third subset of the radar data received after the first or second subsets of the radar data; determine, based on the third subset of the radar data, that the third movement of the user in the radar field comprises a second radar gesture; and in response to the determination that the third movement of the user in the radar field comprises the second radar gesture, present a successful visual animation of the second visual gaming element, the successful visual animation of the second visual gaming element indicating another successful advance of the visual game-play.

  15. The radar-gesture-enabled electronic device of claim 14, wherein the determination, based on the third subset of the radar data, that the third movement of the user in the radar field comprises the second radar gesture further comprises: using the third subset of radar data to detect values of a set of parameters that are associated with the third movement of the user in the radar field; comparing the detected values of the set of parameters to benchmark values for the set of parameters, the benchmark values corresponding to the second radar gesture.

  16. The radar-gesture-enabled electronic device of claim 14, wherein a field of view within which the first radar gesture or the second radar gesture is determined includes volumes within approximately one meter of the radar-gesture-enabled electronic device and within angles of greater than approximately ten degrees measured from a plane of the display of the radar-gesture-enabled electronic device.

  17. The radar-gesture-enabled electronic device of claim 14, wherein the gesture-training module is further configured to: generate, with a machine-learned model, adjusted benchmark values associated with the first radar gesture or the second radar gesture; receive a fourth subset of the radar data corresponding to a fourth movement of the user in the radar field; use the fourth subset of the radar data to detect values of a set of parameters that are associated with the fourth movement of the user in the radar field; compare the detected values of the set of parameters to the adjusted benchmark values; determine, based on the comparison, that the fourth movement of the user in the radar field comprises the first or second radar gesture, and wherein the fourth movement of the user in the radar field is not the first radar gesture or the second radar gesture based on a comparison of the values of the set of parameters to default benchmark values.

  18. The radar-gesture-enabled electronic device of claim 11, wherein the determination, based on the first subset of the radar data, whether the first movement of the user in the radar field comprises the first radar gesture further comprises: using the first subset of the radar data to detect values of a set of parameters that are associated with the first movement of the user in the radar field; comparing the detected values of the set of parameters to benchmark values for the set of parameters, the benchmark values corresponding to the first radar gesture.

  19. The radar-gesture-enabled electronic device of claim 11, wherein the first visual gaming element is presented without textual instructions or non-textual instructions associated with how to perform the first radar gesture.

  20. The radar-gesture-enabled electronic device of claim 11, wherein the first visual gaming element is presented with a supplementary instruction that describes how to perform the first radar gesture, the supplementary instruction comprising either or both of textual instructions or non-textual instructions.

Description

PRIORITY APPLICATION

[0001] This application claims priority under 35 U.S.C. .sctn. 119(e) to U.S. Provisional Patent Application No. 62/910,135 filed Oct. 3, 2019 entitled “Facilitating User-Proficiency in Using Radar Gestures to Interact with an Electronic Device”, the disclosure of which is incorporated in its entirety by reference herein.

BACKGROUND

[0002] Smartphones, wearable computers, tablets, and other electronic devices are relied upon for both personal and business use. Users communicate with them via voice and touch and treat them like a virtual assistant to schedule meetings and events, consume digital media, and share presentations and other documents. Further, machine-learning techniques can help these devices to anticipate some of their users’ preferences for using the devices. For all this computing power and artificial intelligence, however, these devices are still reactive communicators. That is, however “smart” a smartphone is, and however much the user talks to it like it is a person, the electronic device can only perform tasks and provide feedback after the user interacts with the device. The user may interact with the electronic device in many ways, including voice, touch, and other input techniques. As new technical capabilities and features are introduced, the user may have to learn a new input technique or a different way to use an existing input technique. Only after learning these new techniques and methods can the user take advantage of the new features, applications, and functionality that are available. Lack of experience with the new features and input methods often leads to a poor user experience with the device.

SUMMARY

[0003] This document describes techniques and systems that enable facilitating user-proficiency in using radar gestures to interact with an electronic device. The techniques and systems use a radar field to enable an electronic device to accurately determine the presence or absence of a user near the electronic device and to detect a reach or other radar gesture the user makes to interact with the electronic device. Further, the electronic device includes an application that can help the user learn how to properly make the radar gestures that can be used to interact with the electronic device. The application can be a game, a tutorial, or another format that allows users to learn how to make radar gestures that are effective to interact with or control the electronic device. The application can also use machine-learning techniques and models to help the radar system and electronic device better recognize how different users make radar gestures. The application and machine-learning functionality can improve the user’s proficiency in using radar gestures and allow the user to take advantage of the additional functionality and features provided by the availability of the radar gesture, which can result in a better user experience.

[0004] Aspects described below include a method performed by a radar-gesture-enabled electronic device. The method includes presenting a first visual gaming element on a display of the radar-gesture-enabled electronic device. The method also includes receiving first radar data corresponding to a first movement of a user in a radar field provided by a radar system, the radar system included or associated with the radar-gesture-enabled electronic device. The method includes determining, based on the first radar data, whether the first movement of the user in the radar field comprises a first radar gesture. The method further includes, in response to determining that the first movement of the user in the radar field comprises the first radar gesture, presenting a successful visual animation of the first visual gaming element, the successful visual animation of the first visual gaming element indicating a successful advance of the visual game-play. Alternately, the method includes, in response to determining that the first movement of the user in the radar field does not comprise the first radar gesture, presenting an unsuccessful visual animation of the first visual gaming element, the unsuccessful visual animation of the first visual element indicating a failure to advance the visual game-play.

[0005] Other aspects described below include a radar-gesture-enabled electronic device comprising a radar system, a computer processor, and a computer-readable media. The radar system is implemented at least partially in hardware and provides a radar field. The radar system also senses reflections from a user in the radar field, analyzes the reflections from the user in the radar field, and provides radar data based on the analysis of the reflections. The computer-readable media includes stored instructions that can be executed by the one or more computer processors to implement a gesture-training module. The gesture-training module presents, in context of visual game-play, a first visual gaming element on a display of the radar-gesture-enabled electronic device. The gesture-training module also receives a first subset of the radar data which corresponds to a first movement of the user in the radar field. The gesture-training module further determines, based on the first subset of the radar data, whether the first movement of the user in the radar field comprises a first radar gesture. In response to a determination that the first movement of the user in the radar field comprises the first radar gesture, the gesture-training module presents a successful visual animation of the first visual gaming element, the successful visual animation of the first visual gaming element indicating a successful advance of the visual game-play. Alternately, in response to a determination that the first movement of the user in the radar field does not comprise the first radar gesture, the gesture-training module presents an unsuccessful visual animation of the first visual gaming element, the unsuccessful visual animation of the first visual element indicating a failure to advance the visual game-play.

[0006] In other aspects, a radar-gesture-enabled electronic device comprising a radar system, a computer processor, and a computer-readable media is described. The radar system is implemented at least partially in hardware and provides a radar field. The radar system also senses reflections from a user in the radar field, analyzes the reflections from the user in the radar field, and provides radar data based on the analysis of the reflections. The radar-gesture-enabled electronic device includes means for presenting, in context of visual game-play, a first visual gaming element on a display of the radar-gesture-enabled electronic device. The radar-gesture-enabled electronic device also includes means for receiving a first subset of the radar data which corresponds to a first movement of the user in the radar field. The radar-gesture-enabled electronic device also includes means for determining, based on the first subset of the radar data, whether the first movement of the user in the radar field comprises a first radar gesture. The radar-gesture-enabled electronic device also includes means for presenting, in response to a determination that the first movement of the user in the radar field comprises the first radar gesture, a successful visual animation of the first visual gaming element, the successful visual animation of the first visual gaming element indicating a successful advance of the visual game-play. Alternately, the radar-gesture-enabled electronic device includes means for presenting, in response to a determination that the first movement of the user in the radar field does not comprise the first radar gesture, an unsuccessful visual animation of the first visual gaming element, the unsuccessful visual animation of the first visual element indicating a failure to advance the visual game-play.

[0007] This summary is provided to introduce simplified concepts of facilitating user-proficiency in using radar gestures to interact with an electronic device. The simplified concepts are further described below in the Detailed Description. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended for use in determining the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Aspects of facilitating user-proficiency in using radar gestures to interact with an electronic device are described with reference to the following drawings. The same numbers are used throughout the drawings to reference like features and components:

[0009] FIG. 1 illustrates an example operating environment in which techniques that enable facilitating user-proficiency in using radar gestures to interact with an electronic device can be implemented.

[0010] FIG. 2 illustrates an example implementation of facilitating user-proficiency in using radar gestures to interact with an electronic device in the example operating environment of FIG. 1.

[0011] FIG. 3 illustrates another example implementation of facilitating user-proficiency in using radar gestures to interact with an electronic device in the example operating environment of FIG. 1.

[0012] FIG. 4 illustrates an example implementation of an electronic device, including a radar system, through which facilitating user-proficiency in using radar gestures to interact with an electronic device can be implemented.

[0013] FIG. 5 illustrates an example implementation of the radar system of FIGS. 1 and 4.

[0014] FIG. 6 illustrates example arrangements of receiving antenna elements for the radar system of FIG. 5.

[0015] FIG. 7 illustrates additional details of an example implementation of the radar system of FIGS. 1 and 4.

[0016] FIG. 8 illustrates an example scheme that can be implemented by the radar system of FIGS. 1 and 4.

[0017] FIG. 9 illustrates an example method that uses a tutorial environment with visual elements and visual feedback elements for facilitating user-proficiency in using radar gestures to interact with an electronic device.

[0018] FIGS. 10-22 illustrate examples of the visual elements and visual feedback elements used with the tutorial environment methods described in FIG. 9.

[0019] FIG. 23 illustrates another example method that uses a game environment that includes visual gaming elements and animations of the visual gaming elements for facilitating user-proficiency in using radar gestures to interact with an electronic device.

[0020] FIGS. 24-33 illustrate examples of the visual gaming elements and the animations of the visual gaming elements used with the gaming environment methods described in FIG. 23.

[0021] FIG. 34 illustrates an example computing system that can be implemented as any type of client, server, and/or electronic device as described with reference to FIGS. 1-33 to implement, or in which techniques may be implemented that enable, facilitating user-proficiency in using radar gestures to interact with an electronic device.

DETAILED DESCRIPTION

[0022] Overview

[0023] This document describes techniques and systems that enable facilitating user-proficiency in using radar gestures to interact with an electronic device. The described techniques employ a radar system that detects and determines radar-based touch-independent gestures (radar gestures) that are made by the user to interact with the electronic device and applications or programs running on the electronic device. In order for the radar gestures to be used to control or interact with the electronic device, the user must properly make or perform the individual radar gestures (otherwise, there is a risk of radar gestures being ignored or of non-gestures being detected as gestures). The described techniques therefore also use an application that can present a tutorial or game environment that allows the user to learn and practice radar gestures in a natural way. The tutorial or game environments also provide visual feedback elements that give the user feedback when radar gestures are properly made and when the radar gestures are not properly made, which makes the learning and practicing a pleasant and enjoyable experience for the user.

[0024] In this description, the terms “radar-based touch-independent gesture,” “3D gesture,” or “radar gesture” refer to the nature of a gesture in space, away from the electronic device (e.g., the gesture does not require the user to touch the device, though the gesture does not preclude touch). The radar gesture itself may often only have an active informational component that lies in two dimensions, such as a radar gesture consisting of an upper-left-to-lower-right swipe in a plane, but because the radar gesture also has a distance from the electronic device (a “third” dimension or depth), the radar gestures discussed herein can be generally be considered three-dimensional. Applications that can receive control input through radar-based touch-independent gestures are referred to as radar-gesture applications or radar-enabled applications.

[0025] Consider an example smartphone that includes the described radar system and tutorial (or game) application. In this example, the user launches the tutorial or game and interacts with elements presented on a display of the electronic device. The user interacts with the elements or plays the game, which requires the user to make radar gestures. When the user properly makes the radar gesture, the tutorial advances or game-play is extended (or progresses). When the user makes the radar gesture improperly, the application provides other feedback to help the user make the gesture. The radar gesture is determined to be successful (e.g., properly made) based on various criteria that may change depending on factors such as the type of radar-gesture application the gesture is to be used with or the type of radar gesture (e.g., a horizontal swipe, a vertical swipe, or an expanding or contracting pinch). For example, the criteria may include the shape of the radar gesture, the velocity of the radar gesture, or how close the user’s hand is to the electronic device during the completion of the radar gesture.

[0026] The described techniques and systems employ a radar system, along with other features, to provide a useful and rewarding user experience, including visual feedback and game-play, based on the user’s gestures and the operation of a radar-gesture application on the electronic device. Rather than relying only on the user’s knowledge and awareness of a particular radar-gesture application, the electronic device can provide feedback to the user to indicate the success or failure of a radar gesture. Some conventional electronic devices may include instructions for using different input methods (e.g., as part of the device packaging or documentation). For example, the electronic device may provide a few diagrams or a website address in a packaging insert. In some cases, the application may also have “help” functionality. The conventional electronic device, however, typically cannot provide a useful and rich ambient experience that can educate the user about the capabilities of the electronic device and the user’s interactions with the electronic device.

[0027] These are but a few examples of how the described techniques and systems may be used to enable facilitating user-proficiency in using radar gestures to interact with an electronic device, other examples and implementations of which are described throughout this document. The document now turns to an example operating environment, after which example devices, methods, and systems are described.

[0028] Operating Environment

[0029] FIG. 1 illustrates an example environment 100 in which techniques that enable facilitating user-proficiency in using radar gestures to interact with an electronic device can be implemented. The example environment 100 includes an electronic device 102, which includes, or is associated with, a persistent radar system 104, a persistent gesture-training module 106 (gesture-training module 106), and, optionally, one or more non-radar sensors 108 (non-radar sensor 108). The term “persistent,” with reference to the radar system 104 or the gesture-training module 106, means that no user interaction is required to activate the radar system 104 (which may operate in various modes, such as a dormant mode, an engaged mode, or an active mode) or the gesture-training module 106. In some implementations, the “persistent” state may be paused or turned off (e.g., by a user). In other implementations, the “persistent” state may be scheduled or otherwise managed in accordance with one or more parameters of the electronic device 102 (or another electronic device). For example, the user may schedule the “persistent” state such that it is only operational during daylight hours, even though the electronic device 102 is on both at night and during the day. The non-radar sensor 108 can be any of a variety of devices, such as an audio sensor (e.g., a microphone), a touch-input sensor (e.g., a touchscreen), a motion sensor, or an image-capture device (e.g., a camera or video-camera).

[0030] In the example environment 100, the radar system 104 provides a radar field 110 by transmitting one or more radar signals or waveforms as described below with reference to FIGS. 5-8. The radar field 110 is a volume of space from which the radar system 104 can detect reflections of the radar signals and waveforms (e.g., radar signals and waveforms reflected from an object in the volume of space). The radar field 110 may be configured in multiple shapes, such as a sphere, a hemisphere, an ellipsoid, a cone, one or more lobes, or an asymmetric shape (e.g., that can cover an area on either side of an obstruction that is not penetrable by radar). The radar system 104 also enables the electronic device 102, or another electronic device, to sense and analyze reflections from an object or movement in the radar field 110.

[0031] Some implementations of the radar system 104 are particularly advantageous as applied in the context of smartphones, such as the electronic device 102, for which there is a convergence of issues such as a need for low power, a need for processing efficiency, limitations in a spacing and layout of antenna elements, and other issues, and are even further advantageous in the particular context of smartphones for which radar detection of fine hand gestures is desired. Although the implementations are particularly advantageous in the described context of the smartphone for which fine radar-detected hand gestures are required, it is to be appreciated that the applicability of the features and advantages of the present invention is not necessarily so limited, and other implementations involving other types of electronic devices (e.g., as described with reference to FIG. 4) are also within the scope of the present teachings.

[0032] With reference to interaction with or by the radar system 104, the object may be any of a variety of objects from which the radar system 104 can sense and analyze radar reflections, such as wood, plastic, metal, fabric, a human body, or a portion of a human body (e.g., a foot, hand, or finger of a user of the electronic device 102). As shown in FIG. 1, the object is a user’s hand 112 (user 112). Based on the analysis of the reflections, the radar system 104 can provide radar data that includes various types of information associated with the radar field 110 and the reflections from the user 112 (or a portion of the user 112), as described with reference to FIGS. 5-8 (e.g., the radar system 104 can pass the radar data to other entities, such as the gesture-training module 106).

[0033] The radar data can be continuously or periodically provided over time, based on the sensed and analyzed reflections from the object (e.g., the user 112 or the portion of the user 112 in the radar field 110). A position of the user 112 can change over time (e.g., the object in the radar field may move within the radar field 110), and the radar data can thus vary over time corresponding to the changed positions, reflections, and analyses. Because the radar data may vary over time, the radar system 104 provides radar data that includes one or more subsets of radar data that correspond to different periods of time. For example, the radar system 104 can provide a first subset of the radar data corresponding to a first time-period, a second subset of the radar data corresponding to a second time-period, and so forth. In some cases, different subsets of the radar data may overlap, entirely or in part (e.g., one subset of the radar data may include some or all of the same data as another subset of the radar data).

[0034] In some implementations, the radar system 104 can provide the radar field 110 such that a field of view (e.g., a volume within which the electronic device 102, the radar system 104, or the gesture-training module 106 can determine radar gestures) includes volumes around the electronic device within approximately one meter of the electronic device 102 and within angles of greater than approximately ten degrees measured from the plane of a display of the electronic device. For example, a gesture can be made approximately one meter from the electronic device 102 and at an angle of approximately ten degrees (as measured from the plane of the display 114). In other words, a field of view of the radar system 104 may include approximately 160 degrees of radar field volume that is approximately normal to a plane or surface of the electronic device.

[0035] The electronic device 102 can also include a display 114 and an application manager 116. The display 114 can include any suitable display device, such as a touchscreen, a liquid crystal display (LCD), thin film transistor (TFT) LCD, an in-plane switching (IPS) LCD, a capacitive touchscreen display, an organic light-emitting diode (OLED) display, an active-matrix organic light-emitting diode (AMOLED) display, super AMOLED display, and so forth. The display 114 is used to display visual elements that are associated with various modes of the electronic device 102, which are described in further detail with reference to FIGS. 10-33. The application manager 116 can communicate and interact with applications operating on the electronic device 102 to determine and resolve conflicts between applications (e.g., processor resource usage, power usage, or access to other components of the electronic device 102). The application manager 116 can also interact with applications to determine the applications’ available input modes, such as touch, voice, or radar gestures (and types of radar gestures), and communicate the available modes to the gesture-training module 106.

[0036] The electronic device 102 can detect movements of the user 112 within the radar field 110, such as for radar gesture detection. For instance, the gesture-training module 106 (independently or through the application manager 116) can determine that an application operating on the electronic device has a capability to receive a control input corresponding to a radar gesture (e.g., is a radar-gesture application) and what types of gestures the radar-gesture application can receive. The radar gestures may be based on (or determined through) the radar data and received through the radar system 104. For example, the gesture-training module 106 can present the tutorial or game environment to a user and then the gesture-training module 106 (or the radar system 104) can use one or more subsets of the radar data to detect a motion or movement performed by a portion of the user 112, such as a hand, or an object, that is within a gesture zone 118 of the electronic device 102. The gesture-training module 106 can then determine whether the user’s motion is a radar gesture. For example, the electronic device also includes a gesture library 120. The gesture library 120 is a memory device or location that can store data or information related to known radar gestures or radar gesture templates. The gesture-training module 106 can compare radar data that is associated with movements of the user 112 within the gesture zone 118 to the data or information stored in the gesture library 120 to determine whether the movement of the user 112 is a radar gesture. Additional details of the gesture zone 118 and the gesture library 120 are described below.

[0037] The gesture zone 118 is a region or volume around the electronic device 102 within which the radar system 104 (or another module or application) can detect a motion by the user or a portion of the user (e.g., the user’s hand 112) and determine whether the motion is a radar gesture. The gesture zone of the radar field is a smaller area or region than the radar field (e.g., the gesture zone has a smaller volume than the radar field and is within the radar field). For example, the gesture zone 118 can be a fixed volume around the electronic device that has a static size and/or shape (e.g., a threshold distance around the electronic device 102, such as within three, five, seven, nine, or twelve inches) that is predefined, variable, user-selectable, or determined via another method (e.g., based on power requirements, remaining battery life, imaging/depth sensor, or another factor). In addition to the advantages related to the field of view of the radar system 104, the radar system 104 (and associated programs, module, and managers) allows the electronic device 102 to detect the user’s movements and determine radar gestures in lower-light or no-light environments, because the radar system does not need light to operate.

[0038] In other cases, the gesture zone 118 may be a volume around the electronic device that is dynamically and automatically adjustable by the electronic device 102, the radar system 104, or the gesture-training module 106, based on factors such as the velocity or location of the electronic device 102, a time of day, a state of an application running on the electronic device 102, or another factor. While the radar system 104 can detect objects within the radar field 110 at greater distances, the gesture zone 118 helps the electronic device 102 and the radar-gesture applications to distinguish between intentional radar gestures by the user and other kinds of motions that may resemble radar gestures, but are not intended as such by the user. The gesture zone 118 may be configured with a threshold distance, such as within approximately three, five, seven, nine, or twelve inches. In some cases, the gesture zone may extend different threshold distances from the electronic device in different directions (e.g., it can have a wedged, oblong, ellipsoid, or asymmetrical shape). The size or shape of the gesture zone can also vary over time or be based on other factors such as a state of the electronic device (e.g., battery level, orientation, locked or unlocked), or an environment (such as in a pocket or purse, in a car, or on a flat surface).

[0039] In some implementations, the gesture-training module 106 can be used to provide a tutorial or game environment within which the user 112 can interact with the electronic device 102 using radar gestures, in order to learn and practice making radar gestures. For example, the gesture-training module can present an element on the display 114 that can be used to teach the user how to make and use radar gestures. The element can be any suitable element, such as a visual element, a visual gaming element, or a visual feedback element. FIG. 1 illustrates an example visual element 122, an example visual gaming element 124, and an example visual feedback element 126. For visual brevity in FIG. 1, the examples are represented with generic shapes. These example elements, however, can take any of a variety of forms, such as an abstract shape, a geometric shape, a symbol, a video image (e.g., an embedded video presented on the display 114), or a combination of one or more forms. In other cases, the element can be a real or fictional character, such a person or animal (real or mythological), or a media or game character such as a Pikachu.TM.. Additional examples and details related to these elements are described with reference to FIGS. 2-33.

[0040] Consider an example illustrated in FIG. 2, which shows the user 112 within the gesture zone 118. In FIG. 2, an example visual element 122-1 (shown as a ball component and a dog component) is presented on the display 114. In this example, assume that the gesture-training module 106 is presenting the visual element 122-1 to request that the user 112 make a left-to-right swiping radar gesture (e.g., to train the user to make that gesture). Further assume that the visual element 122-1 is initially presented with the ball near a left edge of the display 114, as shown by a dashed-line representation of the ball component, and with the dog waiting near a right edge of the display 114. Continuing the example, the user 112 makes a hand-movement from left to right, as shown by an arrow 202. Assume that the gesture-training module 106 determines that the user’s movement is the left-to-right swiping radar gesture. In response to the radar gesture, the gesture-training module 106 can provide an example visual feedback element 126-1 that indicates that the user successfully performed the requested left-to-right radar gesture. For example, the visual feedback element 126-1 can be an animation of the visual element 122-1 in which the ball component of the visual element 122-1 moves toward the dog component of the visual element 122-1 (from left to right) as shown by another arrow 204.

[0041] Consider another example illustrated in FIG. 3, which shows the user 112 within the gesture zone 118. In FIG. 3, an example visual gaming element 124-1 (shown as a basketball component and a basket component) is presented on the display 114. In this example, assume that the gesture-training module 106 is presenting the visual gaming element 124-1 to request that the user 112 make a left-to-right swiping radar gesture (e.g., to train the user to make that gesture). Further assume that the visual gaming element 124-1 is initially presented with the basketball component near a left edge of the display 114, as shown by a dashed-line representation of the basketball component, and the basket component is positioned near a right edge of the display 114. Continuing the example, the user 112 makes a hand-movement from left to right, as shown by an arrow 302. Assume that the gesture-training module 106 determines that the user’s movement is the left-to-right swiping radar gesture. In response to the radar gesture, the gesture-training module 106 can provide an example visual feedback element 126-2 that indicates that the user successfully performed the requested left-to-right radar gesture. For example, the visual feedback element 126-2 can be a successful animation of the visual gaming element 124-1 in which the basketball component of the visual gaming element 124-1 moves toward the basket component of the visual gaming element 124-1 (from left to right) as shown by another arrow 304.

[0042] In either of the above examples 200 or 300, the gesture-training module 106 can also determine that the user’s movement is not the requested gesture. In response to the determination that the movement is not the requested radar gesture, the gesture-training module 106 can provide another visual feedback element that indicates that the user did not successfully perform the requested left-to-right radar gesture (not illustrated in FIG. 2 or FIG. 3). Additional examples of the visual elements 122, visual gaming elements 124, and visual feedback elements 126 are described with reference to FIGS. 10-22 and 24-33. These examples show how the described techniques, including the visual elements 122, the visual gaming elements 124, and the visual feedback elements 126 can be used to provide the user with a natural and delightful opportunity to learn and practice radar gestures, which can improve the experience of the user 112 with the electronic device 102 and radar-gesture applications that are running on the electronic device 102.

[0043] In more detail, consider FIG. 4, which illustrates an example implementation 400 of the electronic device 102 (including the radar system 104, the gesture-training module 106, the non-radar sensor 108, the display 114, the application manager 116, and the gesture library 120) that can implement aspects of facilitating user-proficiency in using radar gestures to interact with an electronic device. The electronic device 102 of FIG. 4 is illustrated with a variety of example devices, including a smartphone 102-1, a tablet 102-2, a laptop 102-3, a desktop computer 102-4, a computing watch 102-5, a gaming system 102-6, computing spectacles 102-7, a home-automation and control system 102-8, a smart refrigerator 102-9, and an automobile 102-10. The electronic device 102 can also include other devices, such as televisions, entertainment systems, audio systems, drones, track pads, drawing pads, netbooks, e-readers, home security systems, and other home appliances. Note that the electronic device 102 can be a wearable device, a non-wearable but mobile device, or a relatively immobile device (e.g., desktops and appliances). The term “wearable device,” as used in this disclosure, refers to any device that is capable of being worn at, on or in proximity to a person’s body, such as a wrist, ankle, waist, chest, or other body part or prosthetic (e.g., watch, bracelet, ring, necklace, other jewelry, eyewear, footwear, glove, headband or other headware, clothing, goggles, contact lens).

[0044] In some implementations, exemplary overall lateral dimensions of the electronic device 102 can be approximately eight centimeters by approximately fifteen centimeters. Exemplary footprints of the radar system 104 can be even more limited, such as approximately four millimeters by six millimeters with antennas included. This requirement for such a limited footprint for the radar system 104 is to accommodate the many other desirable features of the electronic device 102 in such a space-limited package (e.g., a fingerprint sensor, the non-radar sensor 108, and so forth). Combined with power and processing limitations, this size requirement can lead to compromises in the accuracy and efficacy of radar-gesture detection, at least some of which can be overcome in view of the teachings herein.

[0045] The electronic device 102 also includes one or more computer processors 402 and one or more computer-readable media 404, which includes memory media and storage media. Applications and/or an operating system (not shown) implemented as computer-readable instructions on the computer-readable media 404 can be executed by the computer processors 402 to provide some or all of the functionalities described herein. For example, the processors 402 can be used to execute instructions on the computer-readable media 404 to implement the gesture-training module 106 and/or the application manager 116. The electronic device 102 may also include a network interface 406. The electronic device 102 can use the network interface 406 for communicating data over wired, wireless, or optical networks. By way of example and not limitation, the network interface 406 may communicate data over a local-area-network (LAN), a wireless local-area-network (WLAN), a personal-area-network (PAN), a wide-area-network (WAN), an intranet, the Internet, a peer-to-peer network, point-to-point network, or a mesh network.

[0046] Various implementations of the radar system 104 can include a System-on-Chip (SoC), one or more Integrated Circuits (ICs), a processor with embedded processor instructions or configured to access processor instructions stored in memory, hardware with embedded firmware, a printed circuit board with various hardware components, or any combination thereof. The radar system 104 can operate as a monostatic radar by transmitting and receiving its own radar signals.

[0047] In some implementations, the radar system 104 may also cooperate with other radar systems 104 that are within an external environment to implement a bistatic radar, a multistatic radar, or a network radar. Constraints or limitations of the electronic device 102, however, may impact a design of the radar system 104. The electronic device 102, for example, may have limited power available to operate the radar, limited computational capability, size constraints, layout restrictions, an exterior housing that attenuates or distorts radar signals, and so forth. The radar system 104 includes several features that enable advanced radar functionality and high performance to be realized in the presence of these constraints, as further described below with respect to FIG. 5. Note that in FIG. 1 and FIG. 4, the radar system 104, the gesture-training module 106, the application manager 116, and the gesture library 120 are illustrated as part of the electronic device 102. In other implementations, one or more of the radar system 104, the gesture-training module 106, the application manager 116, or the gesture library 120 may be separate or remote from the electronic device 102.

[0048] These and other capabilities and configurations, as well as ways in which entities of FIG. 1 act and interact, are set forth in greater detail below. These entities may be further divided, combined, and so on. The environment 100 of FIG. 1 and the detailed illustrations of FIG. 2 through FIG. 34 illustrate some of many possible environments and devices capable of employing the described techniques. FIGS. 5-8 describe additional details and features of the radar system 104. In FIGS. 5-8, the radar system 104 is described in the context of the electronic device 102, but as noted above, the applicability of the features and advantages of the described systems and techniques are not necessarily so limited, and other implementations involving other types of electronic devices may also be within the scope of the present teachings.

[0049] FIG. 5 illustrates an example implementation 500 of the radar system 104 that can be used to enable facilitating user-proficiency in using radar gestures to interact with an electronic device. In the example 500, the radar system 104 includes at least one of each of the following components: a communication interface 502, an antenna array 504, a transceiver 506, a processor 508, and a system media 510 (e.g., one or more computer-readable storage media). The processor 508 can be implemented as a digital signal processor, a controller, an application processor, another processor (e.g., the computer processor 402 of the electronic device 102), or some combination thereof. The system media 510, which may be included within, or be separate from, the computer-readable media 404 of the electronic device 102, includes one or more of the following modules: an attenuation mitigator 514, a digital beamformer 516, an angle estimator 518, or a power manager 520. These modules can compensate for, or mitigate the effects of, integrating the radar system 104 within the electronic device 102, thereby enabling the radar system 104 to recognize small or complex gestures, distinguish between different orientations of the user, continuously monitor an external environment, or realize a target false-alarm rate. With these features, the radar system 104 can be implemented within a variety of different devices, such as the devices illustrated in FIG. 4.

[0050] Using the communication interface 502, the radar system 104 can provide radar data to the gesture-training module 106. The communication interface 502 may be a wireless or wired interface based on the radar system 104 being implemented separate from, or integrated within, the electronic device 102. Depending on the application, the radar data may include raw or minimally processed data, in-phase and quadrature (I/Q) data, range-Doppler data, processed data including target location information (e.g., range, azimuth, elevation), clutter map data, and so forth. Generally, the radar data contains information that is usable by the gesture-training module 106 for facilitating user-proficiency in using radar gestures to interact with an electronic device.

[0051] The antenna array 504 includes at least one transmitting antenna element (not shown) and at least two receiving antenna elements (as shown in FIG. 6). In some cases, the antenna array 504 may include multiple transmitting antenna elements to implement a multiple-input multiple-output (MIMO) radar capable of transmitting multiple distinct waveforms at a time (e.g., a different waveform per transmitting antenna element). The use of multiple waveforms can increase a measurement accuracy of the radar system 104. The receiving antenna elements can be positioned in a one-dimensional shape (e.g., a line) or a two-dimensional shape for implementations that include three or more receiving antenna elements. The one-dimensional shape enables the radar system 104 to measure one angular dimension (e.g., an azimuth or an elevation) while the two-dimensional shape enables two angular dimensions to be measured (e.g., both azimuth and elevation). Example two-dimensional arrangements of the receiving antenna elements are further described with respect to FIG. 6.

[0052] FIG. 6 illustrates example arrangements 600 of receiving antenna elements 602. If the antenna array 504 includes at least four receiving antenna elements 602, for example, the receiving antenna elements 602 can be arranged in a rectangular arrangement 604-1 as depicted in the middle of FIG. 6. Alternatively, a triangular arrangement 604-2 or an L-shape arrangement 604-3 may be used if the antenna array 504 includes at least three receiving antenna elements 602.

[0053] Due to a size or layout constraint of the electronic device 102, an element spacing between the receiving antenna elements 602 or a quantity of the receiving antenna elements 602 may not be ideal for the angles at which the radar system 104 is to monitor. In particular, the element spacing may cause angular ambiguities to be present that make it challenging for conventional radars to estimate an angular position of a target. Conventional radars may therefore limit a field of view (e.g., angles that are to be monitored) to avoid an ambiguous zone, which has the angular ambiguities, and thereby reduce false detections. For example, conventional radars may limit the field of view to angles between approximately -45 degrees to 45 degrees to avoid angular ambiguities that occur using a wavelength of 5 millimeters (mm) and an element spacing of 3.5 mm (e.g., the element spacing being 70% of the wavelength). Consequently, the conventional radar may be unable to detect targets that are beyond the 45-degree limits of the field of view. In contrast, the radar system 104 includes the digital beamformer 516 and the angle estimator 518, which resolve the angular ambiguities and enable the radar system 104 to monitor angles beyond the 45-degree limit, such as angles between approximately -90 degrees to 90 degrees, or up to approximately -180 degrees and 180 degrees. These angular ranges can be applied across one or more directions (e.g., azimuth and/or elevation). Accordingly, the radar system 104 can realize low false-alarm rates for a variety of different antenna array designs, including element spacings that are less than, greater than, or equal to half a center wavelength of the radar signal.

[0054] Using the antenna array 504, the radar system 104 can form beams that are steered or un-steered, wide or narrow, or shaped (e.g., as a hemisphere, cube, fan, cone, or cylinder). As an example, the one or more transmitting antenna elements (not shown) may have an un-steered omnidirectional radiation pattern or may be able to produce a wide beam, such as the wide transmit beam 606. Either of these techniques enable the radar system 104 to illuminate a large volume of space. To achieve target angular accuracies and angular resolutions, however, the receiving antenna elements 602 and the digital beamformer 516 can be used to generate thousands of narrow and steered beams (e.g., 2000 beams, 4000 beams, or 6000 beams), such as the narrow receive beam 608. In this way, the radar system 104 can efficiently monitor the external environment and accurately determine arrival angles of reflections within the external environment.

[0055] Returning to FIG. 5, the transceiver 506 includes circuitry and logic for transmitting and receiving radar signals via the antenna array 504. Components of the transceiver 506 can include amplifiers, mixers, switches, analog-to-digital converters, filters, and so forth for conditioning the radar signals. The transceiver 506 can also include logic to perform in-phase/quadrature (I/Q) operations, such as modulation or demodulation. The transceiver 506 can be configured for continuous wave radar operations or pulsed radar operations. A variety of modulations can be used to produce the radar signals, including linear frequency modulations, triangular frequency modulations, stepped frequency modulations, or phase modulations.

[0056] The transceiver 506 can generate radar signals within a range of frequencies (e.g., a frequency spectrum), such as between 1 gigahertz (GHz) and 400 GHz, between 4 GHz and 100 GHz, or between 57 GHz and 63 GHz. The frequency spectrum can be divided into multiple sub-spectra that have a similar bandwidth or different bandwidths. The bandwidths can be on the order of 500 megahertz (MHz), 1 GHz, 2 GHz, and so forth. As an example, different frequency sub-spectra may include frequencies between approximately 57 GHz and 59 GHz, 59 GHz and 61 GHz, or 61 GHz and 63 GHz. Multiple frequency sub-spectra that have a same bandwidth and may be contiguous or non-contiguous may also be chosen for coherence. The multiple frequency sub-spectra can be transmitted simultaneously or separated in time using a single radar signal or multiple radar signals. The contiguous frequency sub-spectra enable the radar signal to have a wider bandwidth while the non-contiguous frequency sub-spectra can further emphasize amplitude and phase differences that enable the angle estimator 518 to resolve angular ambiguities. The attenuation mitigator 514 or the angle estimator 518 may cause the transceiver 506 to utilize one or more frequency sub-spectra to improve performance of the radar system 104, as further described with respect to FIGS. 7 and 8.

[0057] A power manager 520 enables the radar system 104 to conserve power internally or externally within the electronic device 102. In some implementations, the power manager 520 communicates with the gesture-training module 106 to conserve power within either or both of the radar system 104 or the electronic device 102. Internally, for example, the power manager 520 can cause the radar system 104 to collect data using a predefined power mode or a specific gesture-frame update rate. The gesture-frame update rate represents how often the radar system 104 actively monitors the external environment by transmitting and receiving one or more radar signals. Generally speaking, the power consumption is proportional to the gesture-frame update rate. As such, higher gesture-frame update rates result in larger amounts of power being consumed by the radar system 104.

[0058] Each predefined power mode can be associated with a particular framing structure, a particular transmit power level, or particular hardware (e.g., a low-power processor or a high-power processor). Adjusting one or more of these affects the radar system’s 104 power consumption. Reducing power consumption, however, affects performance, such as the gesture-frame update rate and response delay. In this case, the power manager 520 dynamically switches between different power modes such that gesture-frame update rate, response delay and power consumption are managed together based on the activity within the environment. In general, the power manager 520 determines when and how power can be conserved, and incrementally adjusts power consumption to enable the radar system 104 to operate within power limitations of the electronic device 102. In some cases, the power manager 520 may monitor an amount of available power remaining and adjust operations of the radar system 104 accordingly. For example, if the remaining amount of power is low, the power manager 520 may continue operating in a lower-power mode instead of switching to a higher-power mode.

[0059] The lower-power mode, for example, may use a lower gesture-frame update rate on the order of a few hertz (e.g., approximately 1 Hz or less than 5 Hz) and consume power on the order of a few milliwatts (mW) (e.g., between approximately 2 mW and 4 mW). The higher-power mode, on the other hand, may use a higher gesture-frame update rate on the order of tens of hertz (Hz) (e.g., approximately 20 Hz or greater than 10 Hz), which causes the radar system 104 to consume power on the order of several milliwatts (e.g., between approximately 6 mW and 20 mW). While the lower-power mode can be used to monitor the external environment or detect an approaching user, the power manager 520 may switch to the higher-power mode if the radar system 104 determines the user is starting to perform a gesture. Different triggers may cause the power manager 520 to dynamically switch between the different power modes. Example triggers include motion or the lack of motion, appearance or disappearance of the user, the user moving into or out of a designated region (e.g., a region defined by range, azimuth, or elevation), a change in velocity of a motion associated with the user, or a change in reflected signal strength (e.g., due to changes in radar cross section). In general, the triggers that indicate a lower probability of the user interacting with the electronic device 102 or a preference to collect data using a longer response delay may cause a lower-power mode to be activated to conserve power.

[0060] Each power mode can be associated with a particular framing structure. The framing structure specifies a configuration, scheduling, and signal characteristics associated with the transmission and reception of the radar signals. In general, the framing structure is set up such that the appropriate radar data can be collected based on the external environment. The framing structure can be customized to facilitate collection of different types of radar data for different applications (e.g., proximity detection, feature recognition, or gesture recognition). During inactive times throughout each level of the framing structure, the power-manager 520 can turn off the components within the transceiver 506 in FIG. 5 to conserve power. The framing structure enables power to be conserved through adjustable duty cycles within each frame type. For example, a first duty cycle can be based on a quantity of active feature frames relative to a total quantity of feature frames. A second duty cycle can be based on a quantity of active radar frames relative to a total quantity of radar frames. A third duty cycle can be based on a duration of the radar signal relative to a duration of a radar frame.

[0061] Consider an example framing structure (not illustrated) for the lower-power mode that consumes approximately 2 mW of power and has a gesture-frame update rate between approximately 1 Hz and 4 Hz. In this example, the framing structure includes a gesture frame with a duration between approximately 250 ms and 1 second. The gesture frame includes thirty-one pulse-mode feature frames. One of the thirty-one pulse-mode feature frames is in the active state. This results in the duty cycle being approximately equal to 3.2%. A duration of each pulse-mode feature frame is between approximately 8 ms and 32 ms. Each pulse-mode feature frame is composed of eight radar frames. Within the active pulse-mode feature frame, all eight radar frames are in the active state. This results in the duty cycle being equal to 100%. A duration of each radar frame is between approximately 1 ms and 4 ms. An active time within each of the active radar frames is between approximately 32 .rho.s and 128 .rho.s. As such, the resulting duty cycle is approximately 3.2%. This example framing structure has been found to yield good performance results. These good performance results are in terms of good gesture recognition and presence detection while also yielding good power efficiency results in the application context of a handheld smartphone in a low-power state. Based on this example framing structure, the power manager 520 can determine a time for which the radar system 104 is not actively collecting radar data. Based on this inactive time period, the power manager 520 can conserve power by adjusting an operational state of the radar system 104 and turning off one or more components of the transceiver 506, as further described below.

[0062] The power manager 520 can also conserve power by turning off one or more components within the transceiver 506 (e.g., a voltage-controlled oscillator, a multiplexer, an analog-to-digital converter, a phase lock loop, or a crystal oscillator) during inactive time periods. These inactive time periods occur if the radar system 104 is not actively transmitting or receiving radar signals, which may be on the order of microseconds (.mu.s), milliseconds (ms), or seconds (s). Further, the power manager 520 can modify transmission power of the radar signals by adjusting an amount of amplification provided by a signal amplifier. Additionally, the power manager 520 can control the use of different hardware components within the radar system 104 to conserve power. If the processor 508 comprises a lower-power processor and a higher-power processor (e.g., processors with different amounts of memory and computational capability), for example, the power manager 520 can switch between utilizing the lower-power processor for low-level analysis (e.g., implementing the idle mode, detecting motion, determining a location of a user, or monitoring the environment) and the higher-power processor for situations in which high-fidelity or accurate radar data is requested by the gesture-training module 106 (e.g., for implementing the aware mode, the engaged mode, or the active mode, gesture recognition or user orientation).

[0063] Further, the power manager 520 can determine a context of the environment around the electronic device 102. From that context, the power manager 520 can determine which power states are to be made available and how they are configured. For example, if the electronic device 102 is in a user’s pocket, then although the user is detected as being proximate to the electronic device 102, there is no need for the radar system 104 to operate in the higher-power mode with a high gesture-frame update rate. Accordingly, the power manager 520 can cause the radar system 104 to remain in the lower-power mode, even though the user is detected as being proximate to the electronic device 102 and cause the display 114 to remain in an off or other lower-power state. The electronic device 102 can determine the context of its environment using any suitable non-radar sensor 108 (e.g., gyroscope, accelerometer, light sensor, proximity sensor, capacitance sensor, and so on) in combination with the radar system 104. The context may include time of day, calendar day, lightness/darkness, number of users near the user, surrounding noise level, speed of movement of surrounding objects (including the user) relative to the electronic device 102, and so forth).

[0064] FIG. 7 illustrates additional details of an example implementation 700 of the radar system 104 within the electronic device 102. In the example 700, the antenna array 504 is positioned underneath an exterior housing of the electronic device 102, such as a glass cover or an external case. Depending on its material properties, the exterior housing may act as an attenuator 702, which attenuates or distorts radar signals that are transmitted and received by the radar system 104. The attenuator 702 may include different types of glass or plastics, some of which may be found within display screens, exterior housings, or other components of the electronic device 102 and have a dielectric constant (e.g., relative permittivity) between approximately four and ten. Accordingly, the attenuator 702 is opaque or semi-transparent to a radar signal 706 and may cause a portion of a transmitted or received radar signal 706 to be reflected (as shown by a reflected portion 704). For conventional radars, the attenuator 702 may decrease an effective range that can be monitored, prevent small targets from being detected, or reduce overall accuracy.

[0065] Assuming a transmit power of the radar system 104 is limited, and re-designing the exterior housing is not desirable, one or more attenuation-dependent properties of the radar signal 706 (e.g., a frequency sub-spectrum 708 or a steering angle 710) or attenuation-dependent characteristics of the attenuator 702 (e.g., a distance 712 between the attenuator 702 and the radar system 104 or a thickness 714 of the attenuator 702) are adjusted to mitigate the effects of the attenuator 702. Some of these characteristics can be set during manufacturing or adjusted by the attenuation mitigator 514 during operation of the radar system 104. The attenuation mitigator 514, for example, can cause the transceiver 506 to transmit the radar signal 706 using the selected frequency sub-spectrum 708 or the steering angle 710, cause a platform to move the radar system 104 closer or farther from the attenuator 702 to change the distance 712, or prompt the user to apply another attenuator to increase the thickness 714 of the attenuator 702.

[0066] Appropriate adjustments can be made by the attenuation mitigator 514 based on pre-determined characteristics of the attenuator 702 (e.g., characteristics stored in the computer-readable media 404 of the electronic device 102 or within the system media 510) or by processing returns of the radar signal 706 to measure one or more characteristics of the attenuator 702. Even if some of the attenuation-dependent characteristics are fixed or constrained, the attenuation mitigator 514 can take these limitations into account to balance each parameter and achieve a target radar performance. As a result, the attenuation mitigator 514 enables the radar system 104 to realize enhanced accuracy and larger effective ranges for detecting and tracking the user that is located on an opposite side of the attenuator 702. These techniques provide alternatives to increasing transmit power, which increases power consumption of the radar system 104, or changing material properties of the attenuator 702, which can be difficult and expensive once a device is in production.

[0067] FIG. 8 illustrates an example scheme 800 implemented by the radar system 104. Portions of the scheme 800 may be performed by the processor 508, the computer processors 402, or other hardware circuitry. The scheme 800 can be customized to support different types of electronic devices and radar-based applications (e.g., the gesture-training module 106), and also enables the radar system 104 to achieve target angular accuracies despite design constraints.

[0068] The transceiver 506 produces raw data 802 based on individual responses of the receiving antenna elements 602 to a received radar signal. The received radar signal may be associated with one or more frequency sub-spectra 804 that were selected by the angle estimator 518 to facilitate angular ambiguity resolution. The frequency sub-spectra 804, for example, may be chosen to reduce a quantity of sidelobes or reduce an amplitude of the sidelobes (e.g., reduce the amplitude by 0.5 dB, 1 dB, or more). A quantity of frequency sub-spectra can be determined based on a target angular accuracy or computational limitations of the radar system 104.

[0069] The raw data 802 contains digital information (e.g., in-phase and quadrature data) for a period of time, different wavenumbers, and multiple channels respectively associated with the receiving antenna elements 602. A Fast-Fourier Transform (FFT) 806 is performed on the raw data 802 to generate pre-processed data 808. The pre-processed data 808 includes digital information across the period of time, for different ranges (e.g., range bins), and for the multiple channels. A Doppler filtering process 810 is performed on the pre-processed data 808 to generate range-Doppler data 812. The Doppler filtering process 810 may comprise another FFT that generates amplitude and phase information for multiple range bins, multiple Doppler frequencies, and for the multiple channels. The digital beamformer 516 produces beamforming data 814 based on the range-Doppler data 812. The beamforming data 814 contains digital information for a set of azimuths and/or elevations, which represents the field of view for which different steering angles or beams are formed by the digital beamformer 516. Although not depicted, the digital beamformer 516 may alternatively generate the beamforming data 814 based on the pre-processed data 808 and the Doppler filtering process 810 may generate the range-Doppler data 812 based on the beamforming data 814. To reduce a quantity of computations, the digital beamformer 516 may process a portion of the range-Doppler data 812 or the pre-processed data 808 based on a range, time, or Doppler frequency interval of interest.

[0070] The digital beamformer 516 can be implemented using a single-look beamformer 816, a multi-look interferometer 818, or a multi-look beamformer 820. In general, the single-look beamformer 816 can be used for deterministic objects (e.g., point-source targets having a single-phase center). For non-deterministic targets (e.g., targets having multiple phase centers), the multi-look interferometer 818 or the multi-look beamformer 820 are used to improve accuracies relative to the single-look beamformer 816. Humans are an example of a non-deterministic target and have multiple phase centers 822 that can change based on different aspect angles, as shown at 824-1 and 824-2. Variations in the constructive or destructive interference generated by the multiple phase centers 822 can make it challenging for conventional radars to accurately determine angular positions. The multi-look interferometer 818 or the multi-look beamformer 820, however, perform coherent averaging to increase an accuracy of the beamforming data 814. The multi-look interferometer 818 coherently averages two channels to generate phase information that can be used to accurately determine the angular information. The multi-look beamformer 820, on the other hand, can coherently average two or more channels using linear or non-linear beamformers, such as Fourier, Capon, multiple signal classification (MUSIC), or minimum variance distortion less response (MVDR). The increased accuracies provided via the multi-look beamformer 820 or the multi-look interferometer 818 enable the radar system 104 to recognize small gestures or distinguish between multiple portions of the user.

[0071] The angle estimator 518 analyzes the beamforming data 814 to estimate one or more angular positions. The angle estimator 518 may utilize signal-processing techniques, pattern-matching techniques, or machine-learning. The angle estimator 518 also resolves angular ambiguities that may result from a design of the radar system 104 or the field of view the radar system 104 monitors. An example angular ambiguity is shown within an amplitude plot 826 (e.g., amplitude response).

[0072] The amplitude plot 826 depicts amplitude differences that can occur for different angular positions of the target and for different steering angles 710. A first amplitude response 828-1 (illustrated with a solid line) is shown for a target positioned at a first angular position 830-1. Likewise, a second amplitude response 828-2 (illustrated with a dotted line) is shown for the target positioned at a second angular position 830-2. In this example, the differences are considered across angles between -180 degrees and 180 degrees.

[0073] As shown in the amplitude plot 826, an ambiguous zone exists for the two angular positions 830-1 and 830-2. The first amplitude response 828-1 has a highest peak at the first angular position 830-1 and a lesser peak at the second angular position 830-2. While the highest peak corresponds to the actual position of the target, the lesser peak causes the first angular position 830-1 to be ambiguous because it is within some threshold for which conventional radars may be unable to confidently determine whether the target is at the first angular position 830-1 or the second angular position 830-2. In contrast, the second amplitude response 828-2 has a lesser peak at the second angular position 830-2 and a higher peak at the first angular position 830-1. In this case, the lesser peak corresponds to the target’s location.

[0074] While conventional radars may be limited to using a highest peak amplitude to determine the angular positions, the angle estimator 518 instead analyzes subtle differences in shapes of the amplitude responses 828-1 and 828-2. Characteristics of the shapes can include, for example, roll-offs, peak or null widths, an angular location of the peaks or nulls, a height or depth of the peaks and nulls, shapes of sidelobes, symmetry within the amplitude response 828-1 or 828-2, or the lack of symmetry within the amplitude response 828-1 or 828-2. Similar shape characteristics can be analyzed in a phase response, which can provide additional information for resolving the angular ambiguity. The angle estimator 518 therefore maps the unique angular signature or pattern to an angular position.

[0075] The angle estimator 518 can include a suite of algorithms or tools that can be selected according to the type of electronic device 102 (e.g., computational capability or power constraints) or a target angular resolution for the gesture-training module 106. In some implementations, the angle estimator 518 can include a neural network 832, a convolutional neural network (CNN) 834, or a long short-term memory (LS.TM.) network 836. The neural network 832 can have various depths or quantities of hidden layers (e.g., three hidden layers, five hidden layers, or ten hidden layers) and can also include different quantities of connections (e.g., the neural network 832 can comprise a fully connected neural network or a partially-connected neural network). In some cases, the CNN 834 can be used to increase computational speed of the angle estimator 518. The LS.TM. network 836 can be used to enable the angle estimator 518 to track the target. Using machine-learning techniques, the angle estimator 518 employs non-linear functions to analyze the shape of the amplitude response 828-1 or 828-2 and generate angular probability data 838, which indicates a likelihood that the user or a portion of the user is within an angular bin. The angle estimator 518 may provide the angular probability data 838 for a few angular bins, such as two angular bins to provide probabilities of a target being to the left or right of the electronic device 102, or for thousands of angular bins (e.g., to provide the angular probability data 838 for a continuous angular measurement).

[0076] Based on the angular probability data 838, a tracker module 840 produces angular position data 842, which identifies an angular location of the target. The tracker module 840 may determine the angular location of the target based on the angular bin that has a highest probability in the angular probability data 838 or based on prediction information (e.g., previously-measured angular position information). The tracker module 840 may also keep track of one or more moving targets to enable the radar system 104 to confidently distinguish or identify the targets. Other data can also be used to determine the angular position, including range, Doppler, velocity, or acceleration. In some cases, the tracker module 840 can include an alpha-beta tracker, a Kalman filter, a multiple hypothesis tracker (MHT), and so forth.

[0077] A quantizer module 844 obtains the angular position data 842 and quantizes the data to produce quantized angular position data 846. The quantization can be performed based on a target angular resolution for the gesture-training module 106. In some situations, fewer quantization levels can be used such that the quantized angular position data 846 indicates whether the target is to the right or to the left of the electronic device 102 or identifies a 90-degree quadrant the target is located within. This may be sufficient for some radar-based applications, such as user proximity detection. In other situations, a larger number of quantization levels can be used such that the quantized angular position data 846 indicates an angular position of the target within an accuracy of a fraction of a degree, one degree, five degrees, and so forth. This resolution can be used for higher-resolution radar-based applications, such as gesture recognition, or in implementations of the gesture zone, recognition zone, aware mode, engaged mode, or active mode as described herein. In some implementations, the digital beamformer 516, the angle estimator 518, the tracker module 840, and the quantizer module 844 are together implemented in a single machine-learning module.

[0078] These and other capabilities and configurations, as well as ways in which entities of FIG. 1-8 act and interact, are set forth below. The described entities may be further divided, combined, used along with other sensors or components, and so on. In this way, different implementations of the electronic device 102, with different configurations of the radar system 104 and non-radar sensors, can be used to implement aspects of facilitating user-proficiency in using radar gestures to interact with an electronic device. The example operating environment 100 of FIG. 1 and the detailed illustrations of FIGS. 2-8 illustrate but some of many possible environments and devices capable of employing the described techniques.

[0079] Example Methods

[0080] FIGS. 9-22 and 23-33 depict example methods 900 and 2300, which enable facilitating user-proficiency in using radar gestures to interact with an electronic device. The methods 900 and 2300 can be performed with an electronic device that includes, or is associated with, a display, a computer processor, and a radar system that can provide a radar field, such as the electronic device 102 (and the radar system 104). The radar system and radar field can provide radar data, based on reflections of the radar field from objects in the radar field (e.g., the user 112 or a portion of the user 112, such as a hand). For example, the radar data may be generated by, and/or received through, the radar system 104, as described with reference to FIGS. 1-8. The radar data is used to determine interactions of the user with the electronic device, such as a presence of the user in the radar field and gestures made by the user (e.g., radar gestures). Based on the determination of the user’s presence, movements, and gestures, the electronic device can enter and exit different modes of functionality and present different elements on the display, including visual elements, visual gaming elements, and visual feedback elements.

[0081] The visual elements described with reference to the methods 900 and 2300 can enable the electronic device to provide training and practice to a user in performing radar-gesture interactions with the electronic device. Further, the visual elements can provide feedback to the user to indicate the success and efficiency of the user’s radar-gesture interactions with the electronic device. Additional examples of the visual elements are described with reference to FIGS. 10-22 and 24-33.

[0082] The method 900 is shown as a set of blocks that specify operations performed but are not necessarily limited to the order or combinations shown for performing the operations by the respective blocks. Further, any of one or more of the operations may be repeated, combined, reorganized, or linked to provide a wide array of additional and/or alternate methods. In portions of the following discussion, reference may be made to the example operating environment 100 of FIG. 1 or to entities or processes as detailed in FIGS. 2-8, reference to which is made for example only. The techniques are not limited to performance by one entity or multiple entities operating on one device.

[0083] At 902, a visual element and instructions are presented on a display of a radar-gesture-enabled electronic device. The visual element and instructions request a user to perform a gesture proximate to the electronic device. For example, the gesture-training module 106 can present the visual element 122 (which can include the visual element 122-1) and instructions on the display 114 of the electronic device 102. The requested gesture can be a radar-based touch-independent radar gesture (as described above), a touch gesture (e.g., on a touch screen), or another kind of gesture, such as a camera-based touch-independent gesture. The visual element 122 can be any of a variety of suitable elements the user 112 can interact with using the requested gesture (e.g., a radar-gesture). In some cases, for example, the visual element 122 can be a set of objects, such as a ball and a dog or a mouse in a maze. In other cases, the visual element 122 can be characters or objects in a game-play environment, such as an animated character with a task to perform (e.g., a Pikachu) or a car on a racetrack.

[0084] The instructions included with the visual element 122 can take any of a variety of forms (e.g., textual, non-textual, or implicit instructions). For example, the instructions can be text presented on the display 114, separate from the visual element (e.g., a line of text that reads “swipe from left to right to throw the ball to the dog” may be presented along with the ball and dog illustrated in FIG. 1). The non-textual instructions provided by the visual element 122 can be an animation of the visual element 122, audio instructions (e.g., through a speaker associated with the electronic device 102), or another type of non-textual instruction. For example, the non-textual instructions can be an animation of the dog illustrated in FIG. 1 in which the dog wags its tail and jumps into the air, or an animation in which the ball moves toward the dog and the dog catches the ball. In other cases, the instructions can be implicit in the presentation of the visual element 122 (e.g., a dog and a ball presented together can implicitly instruct the user to try to throw the ball to the dog, without additional instruction).

[0085] At 904, radar data corresponding to a movement of the user in a radar field provided by a radar system is received. The radar system may be included or associated with the electronic device, and the movement is proximate to the electronic device. For example, the radar system 104, as described with reference to FIGS. 1-8, may provide the radar data.

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