Abstract: Embodiments for determine a perimeter of a physical space on an electronic device are disclosed. In an embodiment, a device has at least one radar sensor of an array of receivers arranged in a plane that sense depth via radar signal modulation and one or more processors that receive radar sensor data with the at least one radar sensor, perform a comparison between received energy level values for one or more points in a scene from the received radar sensor data, detect one or more reflector points based on the comparison and the one or more reflector points have energy level values that are higher than energy level values attributed to other points in the received radar sensor data, and determine an estimation for a perimeter of a physical space based on the one or more reflector points.

Abstract: Embodiments described herein provide for a technique to enable sensor data gathered by multiple electronic devices, such as smart home devices, to be fused into a single coordinate space to enable a higher sensor resolution at each device. For example, multiple sensor equipped devices may communicate over a network to share sensor data between devices. Each device can combine local sensor data with remote sensor data received from other devices to increase the angular resolution of the detected sensor data. To enable this combination, motion characteristics of commonly detected objects can be used to enable the devices to determine a set of relative positions. Coordinate space transformations can then be computed based on the relative positions. Sensor data can be fused using the determined coordinate space transformations.

Abstract: Systems and methods for determining fine grain motions and vibrations of live and/or inanimate objects are described based on using a radar system. For example, biometric information may be extracted from such vibrations associated with a live object. In different embodiments, processing circuitry may perform different statistical analysis on reflections from the objects. Moreover, the processing circuitry may perform different processing functions based on the statistical analysis to determine the vibrations with high accuracy. Furthermore, the processing circuitry may also select one or multiple target maps based on a field of view of the radar system for a more robust measurement of the vibrations associated with one or multiple objects.

Abstract: The techniques described herein can be used for secure identification of authorized locations for use in multi-factor authentication. A set of historical time-stamped coordinates corresponding to a historical time period can be used to determine a set of authorized locations. A request can be received to determine whether a current location of the first user device is an authorized location. A service can determine whether the current location of the first user device corresponds to one of the set of authorized locations.

Abstract: Embodiments described herein provide techniques to enable spatial sensor data from multiple devices to be fused into a single coordinate space. This fused sensor data can then be processed into a point cloud. Point cloud data can then be transformed to enable the classification of objects detected within the sensor data. Features within multiple feature spaces can be extracted from the point cloud data for use in classification. Classification of objects can also be used to correlate objects detected by multiple sensor equipped devices to determine a coordinate space transformation between those devices.

Abstract: Implementations of the subject technology provide object detection and/or classification for electronic devices. Object detection and/or classification can be performed using a radar sensor of an electronic device. The electronic device may be a portable electronic device. In some examples, object classification using a radar sensor can be based on an identification of user motion using radar signals and/or based on extraction of surface features from the radar signals. In some examples, object classification using a radar sensor can be based on time-varying surface features extracted from the radar signals. Surface features that can be extracted from the radar signals include a radar cross-section (RCS), a micro-doppler signal, a range, and/or one or more angles associated with one or more surfaces of the object.

Abstract: Techniques are described for improving driver efficiency. An example method can include a device accessing sparse location data indicative of one or more geographic locations along a route of the user device during a first time period. The route includes a starting location data point and an ending location data point. The device can access motion data collected by the sensors of the user device. The motion data can be collected by the sensors during the first time period. After a conclusion of the first time period, the device can generate, using the sparse location data and the motion data, a dense data set to reconstruct a route that includes the starting location data point and the ending location data point. The reconstructed route can include second dense location data and velocity data. The device can store the reconstructed route in a local memory of the user device.

Abstract: Embodiments described herein provide for a technique to enable sensor data gathered by multiple electronic devices, such as smart home devices, to be fused into a single coordinate space to enable a higher sensor resolution at each device. For example, multiple sensor equipped devices may communicate over a network to share sensor data between devices. Each device can combine local sensor data with remote sensor data received from other devices to increase the angular resolution of the detected sensor data. To enable this combination, motion characteristics of commonly detected objects can be used to enable the devices to determine a set of relative positions. Coordinate space transformations can then be computed based on the relative positions. Sensor data can be fused using the determined coordinate space transformations.

Abstract: An apparatus and method are described for processing a global navigation satellite system (GNSS) signal, the GNSS comprising multiple satellites, wherein each satellite transmits a respective navigation signal containing a spreading code. The method comprises receiving an incoming signal at a receiver, wherein the incoming signal may contain navigation signals from one or more satellites; encrypting the incoming signal at the receiver using a homomorphic encryption scheme to form an encrypted signal; and transmitting the encrypted signal from the receiver to a remote server.

Abstract: Systems and methods for determining fine grain motions and vibrations of live and/or inanimate objects are described based on using a radar system. For example, biometric information may be extracted from such vibrations associated with a live object. In different embodiments, processing circuitry may perform different statistical analysis on reflections from the objects. Moreover, the processing circuitry may perform different processing functions based on the statistical analysis to determine the vibrations with high accuracy. Furthermore, the processing circuitry may also select one or multiple target maps based on a field of view of the radar system for a more robust measurement of the vibrations associated with one or multiple objects.

Abstract: Systems and methods for determining fine grain motions and vibrations of live and/or inanimate objects are described based on using a radar system. For example, biometric information may be extracted from such vibrations associated with a live object. In different embodiments, processing circuitry may perform different statistical analysis on reflections from the objects. Moreover, the processing circuitry may perform different processing functions based on the statistical analysis to determine the vibrations with high accuracy. Furthermore, the processing circuitry may also select one or multiple target maps based on a field of view of the radar system for a more robust measurement of the vibrations associated with one or multiple objects.

Abstract: Implementations of the subject technology provide object detection and/or classification for electronic devices. Object detection and/or classification can be performed using a radar sensor of an electronic device. The electronic device may be a portable electronic device. In some examples, object classification using a radar sensor can be based on an identification of user motion using radar signals and/or based on extraction of surface features from the radar signals. In some examples, object classification using a radar sensor can be based on time-varying surface features extracted from the radar signals. Surface features that can be extracted from the radar signals include a radar cross-section (RCS), a micro-doppler signal, a range, and/or one or more angles associated with one or more surfaces of the object.

Abstract: Systems and methods for detecting spoofed or illegitimate GNSS signals. A processor receives GNSS data and processes this data to extract acceleration, angular velocity, and height or altitude variation data. For the same time period, sensor data from IMU (inertial measurement unit) sensors and from a barometer are received by the processor. From the sensor data, the processor extracts similar acceleration, angular velocity, and height variation data. These two sets of data are then correlated and correlation coefficients are calculated. These correlation coefficients are then used to calculate a decision statistic. The decision statistic is compared with a predetermined value and, if the decision statistic is below a predetermined value, then the GNSS data is considered to be illegitimate or spoofed.

Abstract: An apparatus and method are described for processing a global navigation satellite system (GNSS) signal, the GNSS comprising multiple satellites, wherein each satellite transmits a respective navigation signal containing a spreading code. The method comprises receiving an incoming signal at a receiver, wherein the incoming signal may contain navigation signals from one or more satellites; encrypting the incoming signal at the receiver using a homomorphic encryption scheme to form an encrypted signal; and transmitting the encrypted signal from the receiver to a remote server.

Abstract: A method of processing offset carrier modulated, OCM, ranging signals in a radionavigation system including a plurality of satellite-borne transmitters and at least one ground-based receiver includes receiving a first radionavigation signal from at least one of the plurality of satellite-borne transmitters and down-converting and digitizing the first radionavigation signal to derive therefrom a first OCM signal SA, receiving a second signal SB synchronously broadcast with the first OCM signal SA, the second signal SB having the same or substantially the same center frequency as the first OCM signal SA, coherently combining the first OCM signal SA with the second signal SB at the receiver to generate a combined signal SC, generating a combined correlation value YC corresponding to a correlation of the combined signal SC with a local replica of the first OCM signal SC, and deriving ranging information based on the combined correlation value YC.

Abstract: The invention provides an atmospheric monitoring and measurement system based on the processing of global navigation satellite system radio-frequency signals. The invention is characterized by an open-loop demodulation architecture to extract amplitude and phase information from the received satellite signals, and a signal processing technique which can provide statistics relating to the amplitude and phase variations induced by the atmosphere.

Abstract: Systems and methods for detecting spoofed or illegitimate GNSS signals. A processor receives GNSS data and processes this data to extract acceleration, angular velocity, and height or altitude variation data. For the same time period, sensor data from IMU (inertial measurement unit) sensors and from a barometer are received by the processor. From the sensor data, the processor extracts similar acceleration, angular velocity, and height variation data. These two sets of data are then correlated and correlation coefficients are calculated. These correlation coefficients are then used to calculate a decision statistic. The decision statistic is compared with a predetermined value and, if the decision statistic is below a predetermined value, then the GNSS data is considered to be illegitimate or spoofed.

Abstract: A method of processing offset carrier modulated, OCM, ranging signals in a radionavigation system including a plurality of satellite-borne transmitters and at least one ground-based receiver includes receiving a first radionavigation signal from at least one of the plurality of satellite-borne transmitters and down-converting and digitizing the first radionavigation signal to derive therefrom a first OCM signal SA, receiving a second signal SB synchronously broadcast with the first OCM signal SA, the second signal SB having the same or substantially the same center frequency as the first OCM signal SA, coherently combining the first OCM signal SA with the second signal SB at the receiver to generate a combined signal SC, generating a combined correlation value YC corresponding to a correlation of the combined signal SC with a local replica of the first OCM signal SC, and deriving ranging information based on the combined correlation value YC.

Abstract: The invention provides an atmospheric monitoring and measurement system based on the processing of global navigation satellite system radio-frequency signals. The invention is characterized by an open-loop demodulation architecture to extract amplitude and phase information from the received satellite signals, and a signal processing technique which can provide statistics relating to the amplitude and phase variations induced by the atmosphere.