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.

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.

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.

A method for determining the location of a first source. A first member is provided. A first tip microphone is attached to a first end of the first member. A first static microphone is provided. An initial frequency is recorded at the static microphone. The first member is rotated at an angular velocity. A tangential distance is calculated from the first tip microphone to the source. A source angle is calculated from the first member to the source. A height of the source is calculated.

A determination of a spatial position of a transmitter which emits a wireless signal is provided. A receiver which moves relative to the transmitter receives the wireless signal and analyses a Doppler shift in the received signal. Information is generated for specifying possible spatial positions of the transmitter based on a point of time when a sign in the Doppler shift changes. In this way, a very simple and efficient determination of possible locations of the transmitter can be achieved.

A LIDAR system includes a waveguide array configured to output a LIDAR output signal such that the LIDAR output signal is reflected by an object located off the LIDAR chip. The system also includes electronics configured to tune a wavelength of the LIDAR output signal such that the direction that the LIDAR output signal travels away from the LIDAR chip changes in response to the tuning of the wavelength by the electronics.

A LIDAR system includes a waveguide array configured to output a LIDAR output signal such that the LIDAR output signal is reflected by an object located off the LIDAR chip. The system also includes electronics configured to tune a wavelength of the LIDAR output signal such that the direction that the LIDAR output signal travels away from the LIDAR chip changes in response to the tuning of the wavelength by the electronics.

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.

The disclosure presents a method that estimates the arrival angles of noncircular signals incident on a sensor array based on the ML principle. The complex multidimensional problem according to the ML is transformed into a series of simple problems through the separation of one from the superimposed signals, which leads to the optimization of the function of the two-variable ? and ? associated with, respectively, the direction and the initial phase of the separated signal. The optimum value of ? is theoretically solved. Then the arrival angle of the separated signal is efficiently estimated through a simple 1-D search with respect to ?. Such an optimization process, updating signal separations, is iterated until the direction estimates converge. The proposed method can be applied also in the presence of Doppler effect.