Apparatus is provided to detect motion of a target reflecting one or more pure tone signals, comprising transmission of one or more pure tone acoustic signals, reception of the signal reflected by a target ensonified by the transmitted signal, and motion detection of the ensonified target from analysis of the Discrete Fourier Transform (DFT) of the received signal, in particular values of the time-variance of energy within adjacent frequency bins in the signal DFT, where the emitted tone has a frequency at the boundary between the two adjacent frequency bins.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for motion detection using a communication channel carrier signal. In one aspect, a method includes, for each of one or more motion detection processors, performing operations comprising: for each of one or more communication channels, wherein each communication channel has a center frequency that is different from the center frequency of each other communication channel: determining mean power levels from two or more power samples at the center frequency, determining a difference between the mean power levels of the two or more power samples at the center frequency, and determining whether physical motion is occurring in a monitored area based on the difference between the mean power levels.

An object detection device is configured to be mounted to a movable body and configured to detect an object present around the movable body, and includes: a wave transmitter configured to transmit a transmission wave corresponding to a transmission signal; a wave receiver configured to receive, as a reception wave, the transmission wave reflected by the object; a relative speed estimation part configured to estimate a relative speed between the movable body and the object; a correlation processing part configured to change, in accordance with the relative speed, a window width of a reference window that defines the number of pulses of the transmission signal to be correlated with a reception signal corresponding to the reception wave when a correlation value corresponding to similarity between the transmission signal and the reception signal is obtained; and a detection part configured to detect information on the object, in a case where the correlation value is determined to indicate similarity at a level equal to or higher than a predetermined level.

An object detection device is configured to be mounted to a movable body and configured to detect an object present around the movable body, and includes: a wave transmitter configured to transmit a transmission wave corresponding to a transmission signal; a wave receiver configured to receive, as a reception wave, the transmission wave reflected by the object; a relative speed estimation part configured to estimate a relative speed between the movable body and the object; a correlation processing part configured to change, in accordance with the relative speed, a window width of a reference window that defines the number of pulses of the transmission signal to be correlated with a reception signal corresponding to the reception wave when a correlation value corresponding to similarity between the transmission signal and the reception signal is obtained; and a detection part configured to detect information on the object, in a case where the correlation value is determined to indicate similarity at a level equal to or higher than a predetermined level.

Gesture recognition is a key requirement for Human Computer Interaction (HCl) and multiple modalities are explored in literature. Conventionally, channel taps are estimated using least square based estimation and tap corresponding to finger motion is tracked. These assume that noise component is negligible and can reduce the tracking accuracy for low SNR. Thus, to mitigate the above-mentioned limitation, the system and method of the present disclosure explore the feasibility of using speaker and microphone setup available in most of smart devices and transmit inaudible frequencies (acoustic) for detecting the human finger level gestures accurately. More specifically, System implements the method for millimeter level finger tracking and low power gesture detection on this tracked gesture. The system uses a subspace based high resolution technique for delay estimation and use microphone pairs to jointly estimate the multi-coordinates of finger movement.

Gesture recognition is a key requirement for Human Computer Interaction (HCl) and multiple modalities are explored in literature. Conventionally, channel taps are estimated using least square based estimation and tap corresponding to finger motion is tracked. These assume that noise component is negligible and can reduce the tracking accuracy for low SNR. Thus, to mitigate the above-mentioned limitation, the system and method of the present disclosure explore the feasibility of using speaker and microphone setup available in most of smart devices and transmit inaudible frequencies (acoustic) for detecting the human finger level gestures accurately. More specifically, System implements the method for millimeter level finger tracking and low power gesture detection on this tracked gesture. The system uses a subspace based high resolution technique for delay estimation and use microphone pairs to jointly estimate the multi-coordinates of finger movement.

Techniques for proximity-sensing devices to detect movement of a person in an environment by emitting pulsed ultrasonic signals into the environment, and detecting a change in the energy measurements of the reflections of the pulsed ultrasonic signals off the person caused by the movement of the person relative to the proximity-sensing devices. In addition to detecting movement, and thus presence, of a person, the proximity-sensing devices may further perform techniques for identifying a direction of movement of the person, and also to perform techniques for identifying a number of people that are in the room. The use of pulsed ultrasonic signals, and monitoring changes in energy in reflections of the emitted signals over time, not only enables movement detection and tracking, but also requires less power and computing resources than continuous emission techniques.

Techniques for proximity-sensing devices to detect movement of a person in an environment by emitting pulsed ultrasonic signals into the environment, and detecting a change in the energy measurements of the reflections of the pulsed ultrasonic signals off the person caused by the movement of the person relative to the proximity-sensing devices. In addition to detecting movement, and thus presence, of a person, the proximity-sensing devices may further perform techniques for identifying a direction of movement of the person, and also to perform techniques for identifying a number of people that are in the room. The use of pulsed ultrasonic signals, and monitoring changes in energy in reflections of the emitted signals over time, not only enables movement detection and tracking, but also requires less power and computing resources than continuous emission techniques.

Aspects presented herein may enable a wireless device to dynamically change the frequencies of its pilot tones based on the distance of one or more objects detected, thereby enabling the wireless device to utilize the advantages of both high frequency pilot tone and low frequency pilot tone. In one aspect, a wireless device transmits a first pilot tone at a first frequency. The wireless device detects whether there is an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone. The wireless device transmits a second pilot tone at a second frequency based on at least one object being detected within the specified distance, where the second frequency is higher than the first frequency. The wireless device calculates a first distance of the at least one object with respect to the wireless device based the second pilot tone.

Aspects presented herein may enable a wireless device to dynamically change the frequencies of its pilot tones based on the distance of one or more objects detected, thereby enabling the wireless device to utilize the advantages of both high frequency pilot tone and low frequency pilot tone. In one aspect, a wireless device transmits a first pilot tone at a first frequency. The wireless device detects whether there is an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone. The wireless device transmits a second pilot tone at a second frequency based on at least one object being detected within the specified distance, where the second frequency is higher than the first frequency. The wireless device calculates a first distance of the at least one object with respect to the wireless device based the second pilot tone.