Abstract: Systems and techniques are described for robust radar-based gesture-recognition. A radar system detects radar-based gestures on behalf of application subscribers. A state machine transitions between multiple states based on inertial sensor data. A no-gating state enables the radar system to output radar-based gestures to application subscribers. The state machine also includes a soft-gating state that prevents the radar system from outputting the radar-based gestures to the application subscribers. A hard-gating state prevents the radar system from detecting radar-based gestures altogether. The techniques and systems enable the radar system to determine when not to perform gesture-recognition, enabling user equipment to automatically reconfigure the radar system to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Abstract: Systems and techniques are described for robust radar-based gesture-recognition. A radar system detects radar-based gestures on behalf of application subscribers. A state machine transitions between multiple states based on inertial sensor data. A no-gating state enables the radar system to output radar-based gestures to application subscribers. The state machine also includes a soft-gating state that prevents the radar system from outputting the radar-based gestures to the application subscribers. A hard-gating state prevents the radar system from detecting radar-based gestures altogether. The techniques and systems enable the radar system to determine when not to perform gesture-recognition, enabling user equipment to automatically reconfigure the radar system to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Abstract: This document describes techniques for radio frequency (RF) based micro-motion tracking. These techniques enable even millimeter-scale hand motions to be tracked. To do so, radar signals are used from radar systems that, with conventional techniques, would only permit resolutions of a centimeter or more.

Abstract: Techniques and apparatuses are described that implement an ultrasonic sensor capable of detecting user presence. This ultrasonic sensor can detect user presence without relying on time-of-flight techniques. In particular, the ultrasonic sensor can determine that a user is present based on the occlusion of at least one receiving transducer (e.g., microphone occlusion), the occlusion of at least one transmitting transducer (e.g., speaker occlusion), or a detected change in an audible noise floor of at least one transducer. In this way, the ultrasonic sensor can continue to detect user presence in situations in which a user occludes one or more transducers of the ultrasonic sensor. The ultrasonic sensor can also control operation of another component within a computing device based on the presence of the user to improve the user experience and/or improve power management.

Abstract: Techniques are described herein that enable advanced gaming and virtual reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or submillimeter scale, for user control actions even when those actions are optically occluded or obscured.

Abstract: This document describes techniques and systems that enable a mobile device-based radar system for applying different power modes to a multi-mode interface. The techniques and systems include a user device having a radar system, and an interaction manager. The radar system generates a radar field, provides radar data, and operates at one of various different radar-power states. The user device analyzes the radar data to detect a presence or movement of a user within the radar field. Responsive to the detection, the radar system changes from a first radar-power state to a second radar-power state. Based on this change, the interaction manager selects a power mode, for a multi-mode interface, that corresponds to the second radar-power state, and applies the selected power mode to the multi-mode interface to provide a corresponding display via a display device.

Abstract: This document describes techniques for radio frequency (RF) based micro-motion tracking. These techniques enable even millimeter-scale hand motions to be tracked. To do so, radar signals are used from radar systems that, with conventional techniques, would only permit resolutions of a centimeter or more.

Abstract: Techniques and apparatuses are described that implement a distributed radar system. The distributed radar system includes two or more radar front-end circuits and at least one processor. The radar front-end circuits are distributed within a device at different positions. By partitioning antennas and transceivers across multiple radar front-end circuits instead of consolidating into a single integrated circuit, individual radar front-end circuits can have a smaller footprint than the single integrated circuit. This smaller footprint enables the radar front-end circuits to be integrated within space-constrained devices. The smaller footprint also provides additional flexibility in positioning the radar front-end circuits away from other components within the device that can cause interference. This can reduce the amount of interference seen by the distributed radar system.

Abstract: Techniques and apparatuses are described for radar angular ambiguity resolution. These techniques enable a target's angular position to be determined from a spatial response that has multiple amplitude peaks. Instead of solely considering which peak has a highest amplitude, the techniques for radar angular ambiguity resolution select a frequency sub-spectrum, or multiple frequency sub-spectrums, that emphasize amplitude or phase differences in the spatial response and analyze an irregular shape of the spatial response across a wide field of view to determine the target's angular position. In this way, each angular position of the target has a unique signature, which the radar system can determine and use to resolve the angular ambiguities. Using these techniques, the radar can have an antenna array element spacing that is greater than half a center wavelength of a reflected radar signal that is used to detect the target.

Abstract: Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing near-range detection. The radar system employs a near-range detection module for detecting objects at near ranges in the presence of interference and a far-range detection module for detecting objects at far ranges. By evaluating separate range intervals, these modules can be designed to achieve a target false-alarm rate and detection performance by tailoring their processing to general characteristics of objects and interference at their respective range intervals. This enables the near-range detection module to detect a near-range object without generating a false detection associated with the interference. By utilizing the near-range detection module and the far-range detection module, the radar system can detect objects at both near and far ranges while achieving a target false-alarm rate.

Abstract: Techniques are described herein that enable advanced gaming and virtual reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or submillimeter scale, for user control actions even when those actions are optically occluded or obscured.

Abstract: Techniques and apparatuses are described that implement face authentication anti-spoofing using ultrasound. In particular, a face-authentication system uses ultrasound to distinguish between a real human face and a presentation attack that uses instruments to present a version of a human face. The face-authentication system includes or communicates with an ultrasonic sensor, which can detect a presentation attack and notify the face-authentication system. In general, the ultrasonic sensor analyzes characteristics of a presented object and determines whether the object represents a human face or a presentation attack instrument. In this way, the ultrasonic sensor can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.

Abstract: Techniques and apparatuses are described that implement face authentication anti-spoofing using ultrasound. In particular, a face-authentication system uses ultrasound to distinguish between a real human face and a presentation attack that uses instruments to present a version of a human face. The face-authentication system includes or communicates with an ultrasonic sensor, which can detect a presentation attack and notify the face-authentication system. In general, the ultrasonic sensor uses power-spectra to evaluate an amount of variance observed over time within at least one receive channel. In this way, the ultrasonic sensor can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.

Abstract: Techniques and apparatuses are described that implement face authentication anti-spoofing using interferometry-based coherence. In particular, a face-authentication system uses ultrasound to distinguish between a real human face and a presentation attack that uses instruments to present a version of a human face. The face-authentication system includes or communicates with an ultrasonic sensor, which can detect a presentation attack and notify the face-authentication system. In general, the ultrasonic sensor uses interferometry to evaluate an amount of coherence (or similarity) between reflections observed by two or more transducers. In this way, the ultrasonic sensor can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.

Abstract: This document describes techniques for fine-motion virtual-reality or augmented-reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or sub-millimeter scale, for user control actions even when those actions are small, fast, or obscured due to darkness or varying light. Further, these techniques enable fine resolution and real-time control, unlike conventional RF-tracking or optical-tracking techniques.

Abstract: Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing angular estimation using machine learning. In particular, a radar system 102 includes an angle-estimation module 504 that employs machine learning to estimate an angular position of one or more objects (e.g., users). By analyzing an irregular shape of the radar system 102's spatial response across a wide field of view, the angle-estimation module 504 can resolve angular ambiguities that may be present based on the angle to the object or based on a design of the radar system 102 to correctly identify the angular position of the object. Using machine-learning techniques, the radar system 102 can achieve a high probability of detection and a low false-alarm rate for a variety of different antenna element spacings and frequencies.

Abstract: This document describes techniques and systems that enable a mobile device-based radar system (104) for providing a multi-mode interface (114). A radar field (110) is used to enable a user device (102, 702) to accurately determine a presence or threshold movement of a user near the user device. The user device provides a multi-mode interface having at least first and second modes and providing a black display or a low-luminosity display in the first mode. The user device detects, based on radar data and during the first mode, a presence or threshold movement by the user relative to the user device and responsively changes the multi-mode interface from the first mode to the second mode. Responsive to the change to the second mode, the user device provides visual feedback corresponding to the implicit interaction by adjusting one or more display parameters of the black display or the low-luminosity display.

Abstract: This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor and/or a movement sensor produces a context of a user equipment. The techniques and systems enable the user equipment to recognize contexts when a radar system can be unreliable and should not be used for gesture-recognition, enabling the user equipment to automatically disable or “gate” the output from the radar system according to context. The user equipment prevents the radar system from transitioning to a high-power state to perform gesture-recognition in contexts where radar data detected by the radar system is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Abstract: Various embodiments dynamically learn user-customizable input gestures. A user can transition a radar-based gesture detection system into a gesture-learning mode. In turn, the radar-based gesture detection system emits a radar field configured to detect a gesture new to the radar-based gesture detection system. The radar-based gesture detection system receives incoming radio frequency (RF) signals generated by the outgoing RF signal reflecting off the gesture, and analyzes the incoming RF signals to learn one or more identifying characteristics about the gesture. Upon learning the identifying characteristics, the radar-based gesture detection system reconfigures a corresponding input identification system to detect the gesture when the one or more identifying characteristics are next identified, and transitions out of the gesture-learning mode.

Abstract: This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor (108) and/or a movement sensor (108) produces a context of a user equipment (102). The techniques and systems enable the user equipment (102) to recognize contexts when a radar system (104) can be unreliable and should not be used for gesture-recognition, enabling the user equipment (102) to automatically disable or “gate” the output from the radar system (104) according to context. The user equipment (102) prevents the radar system (104) from transitioning to a high-power state (1910) to perform gesture-recognition in contexts where radar data detected by the radar system (104) is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.