A field-programmable gate array (FPGA)-based real-time processing system applied to underwater acoustic positioning and realizing reconfigurability and multiple output is provided. The system includes a multi-interface control and command parsing module for automatically completing sample information transmission and command parsing; a finite-state machine (FSM) of sample management for calculating related data and completing splitting, flipping and writing of a sample; a parallel correlation processor group for completing, in parallel, high-performance processing operations regarding a plurality of targets; and a multiple output data former for simultaneously realizing data formation of a multiple output result and outputting a flag bit signal to the outside. A FPGA-based real-time processing control method is also provided that is applied to underwater acoustic positioning and realizing reconfigurability and multiple output. The system and the method are used, such that during a whole realization process, under multiple array elements and multiple targets, high-speed parallel correlation processing is realized, thereby solving problems in terms of real-time performance, universality and anti-noise performance, and effectively realizing high-performance correlation.

A field-programmable gate array (FPGA)-based real-time processing system applied to underwater acoustic positioning and realizing reconfigurability and multiple output is provided. The system includes a multi-interface control and command parsing module for automatically completing sample information transmission and command parsing; a finite-state machine (FSM) of sample management for calculating related data and completing splitting, flipping and writing of a sample; a parallel correlation processor group for completing, in parallel, high-performance processing operations regarding a plurality of targets; and a multiple output data former for simultaneously realizing data formation of a multiple output result and outputting a flag bit signal to the outside. A FPGA-based real-time processing control method is also provided that is applied to underwater acoustic positioning and realizing reconfigurability and multiple output. The system and the method are used, such that during a whole realization process, under multiple array elements and multiple targets, high-speed parallel correlation processing is realized, thereby solving problems in terms of real-time performance, universality and anti-noise performance, and effectively realizing high-performance correlation.

In an embodiment, a transducer controller is configured to apply a damping signal to reduce energy stored in the transducer after the transducer has been driven with a drive signal to form a transmitted acoustic signal.

In an embodiment, a transducer controller is configured to apply a damping signal to reduce energy stored in the transducer after the transducer has been driven with a drive signal to form a transmitted acoustic signal.

Disclosed is a system for selective acoustic sensing, capture, sampling and monitoring. One or more acoustic phase array assemblies, each including a set of microphones and digital processing circuits, wherein at least one of the phase array assemblies may include circuits to facilitate the generation of two or more acoustic beams, in the same or in different directions, concurrently. The outputs of each of the two or more acoustic beams are direction specific audio signals, wherein the direction of each direction specific audio signal corresponds to the direction of the respective beamforming process which generated that direction specific audio signal.

Methods, apparatus, systems, and articles of manufacture to detect the location of sound sources external to computing devices are disclosed. An apparatus, to determine a direction of a source of a sound relative to a computing device, includes a cross-correlation analyzer to generate a vector of values corresponding to a cross-correlation of first and second audio signals corresponding to the sound. The first audio signal is received from a first microphone of the computing device. The second audio signal is received from a second microphone of the computing device. The apparatus also includes a location analyzer to use a machine learning model and a set of the values of the vector to determine the direction of the source of the sound.

Methods, apparatus, systems, and articles of manufacture to detect the location of sound sources external to computing devices are disclosed. An apparatus, to determine a direction of a source of a sound relative to a computing device, includes a cross-correlation analyzer to generate a vector of values corresponding to a cross-correlation of first and second audio signals corresponding to the sound. The first audio signal is received from a first microphone of the computing device. The second audio signal is received from a second microphone of the computing device. The apparatus also includes a location analyzer to use a machine learning model and a set of the values of the vector to determine the direction of the source of the sound.

Methods, apparatus, systems, and articles of manufacture to detect the location of sound sources external to computing devices are disclosed. An apparatus, to determine a direction of a source of a sound relative to a computing device, includes a cross-correlation analyzer to generate a vector of values corresponding to a cross-correlation of first and second audio signals corresponding to the sound. The first audio signal is received from a first microphone of the computing device. The second audio signal is received from a second microphone of the computing device. The apparatus also includes a location analyzer to use a machine learning model and a set of the values of the vector to determine the direction of the source of the sound.

Methods, apparatus, systems, and articles of manufacture to detect the location of sound sources external to computing devices are disclosed. An apparatus, to determine a direction of a source of a sound relative to a computing device, includes a cross-correlation analyzer to generate a vector of values corresponding to a cross-correlation of first and second audio signals corresponding to the sound. The first audio signal is received from a first microphone of the computing device. The second audio signal is received from a second microphone of the computing device. The apparatus also includes a location analyzer to use a machine learning model and a set of the values of the vector to determine the direction of the source of the sound.

A method for recognizing infrasound events includes detecting infrasonic source using one or more microphone arrays each having three equally-spaced infrasound microphones. The method includes identifying, via a data acquisition system (DAS), a level of coherence of the detected infrasonic acoustic signals from each possible pair of microphones and recognizing the infrasound source using the coherence and a time history of the detected signals. The method may include estimating source properties via the DAS, including a magnitude, azimuth angle, and elevation angle, and executing a control action in response to the estimated properties. A system includes the array and the DAS. The array may be positioned above or below ground, and may be connected to one or more aircraft in some embodiments.