A rear side warning system for a vehicle includes at least one processor configured to: sense an external obstacle of the vehicle; classify the external obstacle as either one of a fixed object and a moving object; and control a rear side warning signal of the vehicle based on a result of the classifying of the external obstacle.

An illustrative example method of tracking an object includes detecting one or more points on the object over time to obtain a plurality of detections, determining a position of each of the detections, determining a relationship between the determined positions, and determining an estimated heading angle of the object based on the relationship.

Embodiments of the present disclosure provide systems and methods directed to contactless motion tracking. In operation, a speaker may provide an acoustic signal to, for example, a subject. A microphone array may receive a reflected acoustic signal, where the received reflected signal is responsive to the acoustic signal reflecting off the subject. A computing device may extraction motion data of the subject based on the received reflected acoustic signal. Various motion data extraction methods are described herein. The motion data may include respiration motion, coarse movement motion, respiration rate, and the like. Using the extracted motion data, the processor may identify at least one health condition and/or sleep anomaly corresponding to the subject. In some examples, beamforming is implemented to aid in contactless motion tracking.

Embodiments of the present disclosure provide systems and methods directed to contactless motion tracking. In operation, a speaker may provide an acoustic signal to, for example, a subject. A microphone array may receive a reflected acoustic signal, where the received reflected signal is responsive to the acoustic signal reflecting off the subject. A computing device may extraction motion data of the subject based on the received reflected acoustic signal. Various motion data extraction methods are described herein. The motion data may include respiration motion, coarse movement motion, respiration rate, and the like. Using the extracted motion data, the processor may identify at least one health condition and/or sleep anomaly corresponding to the subject. In some examples, beamforming is implemented to aid in contactless motion tracking.

Described herein are techniques for tracking objects (including human body parts such as a hand), namely: 1) two-state transducer interpolation in acoustic phased-arrays; 2) modulation techniques in acoustic phased-arrays; 3) fast acoustic full matrix capture during haptic effects; 4) time-of-flight depth sensor fusion system; 5) phase modulated spherical wave-fronts in acoustic phased-arrays; 6) long wavelength phase modulation of acoustic field for location and tracking; and 7) camera calibration through ultrasonic range sensing.

Described herein are techniques for tracking objects (including human body parts such as a hand), namely: 1) two-state transducer interpolation in acoustic phased-arrays; 2) modulation techniques in acoustic phased-arrays; 3) fast acoustic full matrix capture during haptic effects; 4) time-of-flight depth sensor fusion system; 5) phase modulated spherical wave-fronts in acoustic phased-arrays; 6) long wavelength phase modulation of acoustic field for location and tracking; and 7) camera calibration through ultrasonic range sensing.

An eye tracking unit that includes one or more transmitters that transmit a signal (e.g., a radar signal or an ultrasonic sound) at an eye, one or more receivers that receive a reflection of the signal generated by interaction of the signal with the eye, and an eye orientation estimation module that estimates an orientation of the eye based on the reflected signal received by the one or more ultrasonic receivers and based on a model of the eye. The eye tracking unit may be part of a head-mounted display (HMD) that includes a display element configured to display content to a user wearing the HMD. The model of the eye may be trained by displaying a visual indicator on the electronic element and detecting a reflected signal corresponding to the eye looking at the visual indicator.

A sensor control device includes a plurality of drive units for oscillating respective transducers included in a plurality of ultrasonic sensors, a driving signal generation section for generating driving signals capable of oscillating the respective plurality of transducers, a control unit having a control signal output section for outputting, to each one of the plurality of drive units, a control signal as an input command for the driving signal to the respective transducer and a bus line configured to connect the control unit to the plurality of drive units in form of a daisy-chain, the bus line being used for bidirectional communication of communication data between the control unit and the plurality of drive units based on preset time-division, the communication data being comprised of a data structure having a first band that allows superimposition of audio data thereon. Control data based on the control signal is included in the first band.

A sensor control device includes a plurality of drive units for oscillating respective transducers included in a plurality of ultrasonic sensors, a driving signal generation section for generating driving signals capable of oscillating the respective plurality of transducers, a control unit having a control signal output section for outputting, to each one of the plurality of drive units, a control signal as an input command for the driving signal to the respective transducer and a bus line configured to connect the control unit to the plurality of drive units in form of a daisy-chain, the bus line being used for bidirectional communication of communication data between the control unit and the plurality of drive units based on preset time-division, the communication data being comprised of a data structure having a first band that allows superimposition of audio data thereon. Control data based on the control signal is included in the first band.

A method comprising: providing an autonomous vehicle (AV) with a first estimated position of a target; directing the AV to travel toward the first estimated position at a constant velocity; receiving echo signals of transmitted sonar signals, the echo signals indicating a range and an azimuth of the target; determining a depth difference of the AV and the target based on the received echo signals, the depth difference being determined based on changes to the range and azimuth of the target over time; and in response to a depth difference existing, re-directing the AV toward a second estimated position of the target generated from the depth difference.