Techniques are provided for audio-based detection and tracking of an acoustic source. A methodology implementing the techniques according to an embodiment includes generating acoustic signal spectra from signals provided by a microphone array, and performing beamforming on the acoustic signal spectra to generate beam signal spectra, using time-frequency masks to reduce noise. The method also includes detecting, by a deep neural network (DNN) classifier, an acoustic event, associated with the acoustic source, in the beam signal spectra. The DNN is trained on acoustic features associated with the acoustic event. The method further includes performing pattern extraction, in response to the detection, to identify time-frequency bins of the acoustic signal spectra that are associated with the acoustic event, and estimating a motion direction of the source relative to the array of microphones based on Doppler frequency shift of the acoustic event calculated from the time-frequency bins of the extracted pattern.

The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to transmit and receive acoustic signals. Due to relative movements between the mobile communication device and the base transmitter unit, frequencies of the received signals shift due to Doppler effect. The mobile communication device is configured to compensate Doppler frequency shifts in the received acoustic signals prior to performing a deconvolution decoding process. The mobile communication device is further configured to compensate Doppler frequency shifts and perform deconvolution decoding process on acoustic signals received from multiple signal transmission paths.

The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to transmit and receive acoustic signals. Due to relative movements between the mobile communication device and the base transmitter unit, frequencies of the received signals shift due to Doppler effect. The mobile communication device is configured to compensate Doppler frequency shifts in the received acoustic signals prior to performing a deconvolution decoding process. The mobile communication device is further configured to compensate Doppler frequency shifts and perform deconvolution decoding process on acoustic signals received from multiple signal transmission paths.

In order to estimate the trajectory of a moving wave source, this trajectory estimation device (10) comprises: an acquisition unit (11) that acquires wave motion data based on wave motion detected by a plurality of sensors (100); a generation unit (12) that generates a spectrogram using the wave motion data; an extraction unit (13) that extracts a Doppler shift from the spectrogram; a selection unit (14) that selects, as a sensor pair, two sensors that satisfy a preset selection condition pertaining to the Doppler shift; and an estimation unit (15) that estimates the trajectory of a wave source, which is the source generating the wave motion, on the basis of the positional relationship between the sensors constituting the sensor pair and the relationship of the Doppler shift between the two sensors constituting the sensor pair.

It is provided a system for localizing a sound source and a method therefor. The system includes a movable unit, being adapted for free movement and being integrated with a microphone; a motion tracking unit; and a processing unit, being adapted for receiving microphone signal and motion tracking unit signal and obtaining information on a direction from which sound from the sound source arrives using the microphone signal and motion tracking unit signal obtained during movement of the movable unit. By having the system and the method therefor, it is helpful for solving at least one of the technical problems: the complexity and a large volume of an acoustic camera for localization of a sound source; the restriction of the movement of the microphone in a sound source localization system.

The invention involves using Doppler shift to locate a leak of a signal from an HFC network. The leaked signal includes a component having a nominal frequency. The invention comprises: (a) moving along a drive route in the area of the network; (b) recording a speed at a number of drive-route points along the drive route; (c) at each point, receiving the component at a received frequency; (d) for each point, measuring the received frequency; (e) for each point, determining a measured Doppler shift from a difference between the received and nominal frequencies; (f) estimating a zero Doppler shift and a zero Doppler shift point based on the measured Doppler shifts; and (g) estimating the leak location based on the estimated zero Doppler shift point.

Systems, apparatuses, and methods are described for operating and maintaining a data network, and for detecting problems such as signal leakage. In one implementation, a computing device may determine, based on availability and location, one or more mobile devices and may cause the mobile devices to detect a wireless signal. The detected wireless signal may be identified as having leaked from a network, such as a wired network, and used to detect the source of leaks.

A practically implementable robust direction-of-arrival (DoA) estimation approach that is resistant to localization errors due to mobility, multipath reflections, impulsive noise, and multiple-access interference. As part of the disclosed invention the inventors consider infrastructure-less 3D localization of autonomous underwater vehicles (AUVs) with no GPS assistance and no availability of global clock synchronization. The proposed method can be extended to challenging communication environments and applied for the localization of assets/objects in space, underground, intrabody, underwater and other complex, challenging, congested and sometimes contested environments. Each AUV leverages known-location beacon signals to self-localize and can simultaneously report its sensor data and measurement location. The approach uses two known location beacon nodes, where the beacons are single-hydrophone acoustic nodes that are deployed at known locations and transmit time-domain coded signals in a spread-spectrum fashion.

A method to detect the presence and location of submarines in a complex marine environment by wavelet denoising, wavelet signal enhancement, by autocorrelation and signal source identification a convolutional neural network.

Systems, apparatuses, and methods are described for operating and maintaining a data network, and for detecting problems such as signal leakage. In one implementation, a computing device may determine, based on availability and location, one or more mobile devices and may cause the mobile devices to detect a wireless signal. The detected wireless signal may be identified as having leaked from a network, such as a wired network, and used to detect the source of leaks.