A peak frequency detection device provided with: an n multiplication unit that multiplies each element of a digital data string by n (n is an integer of 2 or more); an FFT unit that derives, as a virtual peak frequency, a frequency that corresponds to the maximum value of a power spectrum that is obtained by performing a fast Fourier transform of a digital data string of N (N is an integer of a power of 2 and is determined in accordance with a sampling frequency (f.sub.s), a sampling resolution (f.sub.tg), and a time window length (T.sub.tg)) sample frequencies (f.sub.s) that are multiplied by n; and a 1/n multiplication unit that outputs the value of the virtual peak frequency multiplied by 1/n as the peak frequency of the digital data string. The peak frequency detection device satisfies n1/(f.sub.tgT.sub.tg), f.sub.s/(nf.sub.tg)Nf.sub.sT.sub.tg, and f.sub.s>2nf.sub.ch.

A wideband sonar receiver is provided that includes: a selectable bandpass filter adapted to filter a received sonar signal to produce a filtered signal and a correlator adapted to correlate the baseband samples with baseband replica samples to provide a correlated signal. In addition, the wideband sonar receiver may include a shaping filter to shape unshaped received pulses. Finally, a variety of sonar processing algorithms are described with regard to reducing clutter and interference, target detection, and bottom detection.

A wideband sonar receiver is provided that includes: a selectable bandpass filter adapted to filter a received sonar signal to produce a filtered signal and a correlator adapted to correlate the baseband samples with baseband replica samples to provide a correlated signal. In addition, the wideband sonar receiver may include a shaping filter to shape unshaped received pulses. Finally, a variety of sonar processing algorithms are described with regard to reducing clutter and interference, target detection, and bottom detection.

The invention relates to a device with a microphone and a speaker or transducer and processing means to process audio signals from the microphone and for the transducer. Electronic devices and especially mobile devices serve several user interfaces of which the touch screen has revolutionized the market in the past few years. Ultrasonic gesture control has the power to add another interface that fills in for use cases where the touch screen is not reliable. This holds true for medical environments as well as for outdoor use cases just to name two. The invention suggests a different signal processing of the ultrasonic sending and receiving signals in order not to produce audible artefacts.

Examples methods and systems for locating an actor in an environment are described herein. For example, an information system may receive point cloud data representing a cluster of potential actors at a location in the environment. In addition, the information system may also receive location information from a device indicating that the current location of the device is proximate to the location of the cluster of potential actors. Based on movement information from the device that indicates movements of the device, the information system may determine a portion of the point cloud data that displays movements that matches the movement of the device. Using the determined portion of the point cloud, the information system may identify a particular actor of the cluster that corresponds to the device and provide an output signal indicating that the determined portion of the point cloud represents the identified particular actor.

An object detection device including a transmitter transmitting a transmission wave where ultrasonic waves of different frequencies are multiplexed, a receiver receiving a reflected wave produced by the reflection of the transmission wave from an object, a frequency analyzer generating reflected wave frequency information indicating a plurality of frequency components contained in the reflected wave, and separated echo information indicating temporal changes in amplitude value for each of the frequency components contained in the reflected wave, a distance information generator generating distance information about the distance to the object, based on the separated echo information, a Doppler detector that calculates a Doppler frequency, based on the reflected wave frequency information, transmission wave frequency information indicating the frequency components of the transmission wave, and frequency interval information of the interval between the frequency components from the transmission wave, and a correction unit correcting the distance information, based on the Doppler frequency.

To determine a location of a user, a computing device transmits an audio signal via a speaker and receives a reflected audio signal via a microphone. The computing device obtains sensor data from at least one of: one or more positioning sensors, one or more accelerometers, one or more gyroscopes, or one or more inertial measurement units, and determines a location of a user based on (i) a round trip time of the audio signal and the reflected audio signal, and (ii) the sensor data.

The present disclosure belongs to the field of underwater target detection, and in particular, to a method for detecting a moving target based on spatial slices of transformed spatio-temporal frequency space. The method includes: segmenting a target radiated acoustic signal received by an M-element horizontal line array in an underwater acoustic environment with a low signal-to-noise ratio (SNR); performing N-point discrete Fourier transform (DFT) on the received signal on each array element in each period of time; performing frequency domain beamforming on an array signal after each section of DFT, and performing stacking after compensating a phase difference between arrays brought by an azimuth of each primitive element; performing coordinate transformation on a frequency-azimuth-time three-dimensional (3D) matrix space obtained; taking a slice from the obtained frequency-azimuth-time 3D space subjected to the coordinate transformation; and performing segmented Radon transform on the spatial slice obtained to detect the target.

The present disclosure belongs to the field of underwater target detection, and in particular, to a method for detecting a moving target based on spatial slices of transformed spatio-temporal frequency space. The method includes: segmenting a target radiated acoustic signal received by an M-element horizontal line array in an underwater acoustic environment with a low signal-to-noise ratio (SNR); performing N-point discrete Fourier transform (DFT) on the received signal on each array element in each period of time; performing frequency domain beamforming on an array signal after each section of DFT, and performing stacking after compensating a phase difference between arrays brought by an azimuth of each primitive element; performing coordinate transformation on a frequency-azimuth-time three-dimensional (3D) matrix space obtained; taking a slice from the obtained frequency-azimuth-time 3D space subjected to the coordinate transformation; and performing segmented Radon transform on the spatial slice obtained to detect the target.

An error correction method and an error correction device for correcting an error in movement data of an object are provided. The error correction method includes collecting sensing values corresponding to movement of the object for each data frame, based on a predetermined time interval, grouping continuously collected data frames among data frames corresponding to the collected sensing values, normalizing the sensing values based on a minimum value among the sensing values of each of the grouped data frames, using an error detection model, determining whether a previous sensing value is an error value, based on a current sensing value and the previous sensing value collected at a time earlier than the current sensing value among the normalized sensing values, and when the previous sensing value is the error value, correcting the error value based on normal values that are not the error value among the sensing values.