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.

Systems and methods are disclosed for conducting an ultrasonic-based inspection. The systems and methods perform operations comprising: receiving a plurality of scan plan parameters associated with generating an image of at least one flaw within a specimen based on acoustic echo data obtained using full matrix capture (FMC); applying the plurality of scan plan parameters to an acoustic model, the acoustic model configured to determine a two-way pressure response of a plurality of inspection modes based on specular reflection and diffraction phenomena; generating, by the acoustic model based on the plurality of scan plan parameters, an acoustic region of influence (AROI) comprising an acoustic amplitude sensitivity map for a first inspection mode amongst the plurality of inspection modes; and generating, for display, a first image comprising the AROI associated with the first inspection mode for capturing or inspecting the image of the at least one flaw.

The disclosure relates to a computer-implemented method for generating synthetic training data for training of a data-driven ultrasonic sensor model for a given configuration of an ultrasonic sensor system having multiple ultrasonic sensor devices, wherein the training data includes input data representing time-series data of received ultrasonic signals and output data indicating object characteristics of environmental objects in a sensing range of the ultrasonic sensor system; comprising the steps of: providing real training data obtained by a measurement of the given configuration of an ultrasonic sensor system; training of a generator model by means of a training model using the real training data; and using the generator model to generate the synthetic training data by applying a random noise vector as input.

Spectral components of waves having one or more properties other than phase and amplitude that vary monotonically with time at a receiver, and provide retardations or lags in the variation in proportion to the times or distances traveled from the sources of the waves to the receiver. The lags denote the property values prior to departure from a source and are absent in its proximity. Orthogonality of the lags to modulated information makes them useful for ranging and for separation or isolation of signals by their source distances. Lags in frequencies and wavelengths permit multiplication of capacities of physical channels. Constancy of the lagging wavelengths along the entire path from a source to the receiver enables reception through channels or media unusable at the source wavelengths, as well as imaging at wavelengths different from the illumination.

A method for probing by wave propagation, in which an incident wave is emitted into a medium comprising diffusers that can reflect the wave. Signals representing a reflected wave reverberated by the medium from the incident wave are captured, said captured signals being the sum of a simple diffusion component and a multiple diffusion component. The captured signals are treated by separating the multiple diffusion component from the simple diffusion component.

An image processing method for reducing distortion of a depth image may include: obtaining a plurality of original images based on light beams which are emitted to and reflected from a subject; determining original depth values of original depth images obtained from the plurality of original images, based on phase delays of the light beams, the reflected light beams comprising multi-reflective light beams that distort the original depth values; determining imaginary intensities of the multi-reflective light beams with respective to each phase of the multi-reflective light beams, based on regions having intensities greater than a predetermined intensity in the original depth images; correcting the original depth values of the original depth images, based on the imaginary intensities of the multi-reflective light beams; and generating corrected depth images based on the corrected original depth values.

A method for processing ultrasonic signals includes: controlling a plurality of emission transducers for L successive emissions of ultrasonic waves; controlling N reception transducers to simultaneously receive and for a predetermined time, for each successive emission, N measurement signals; obtaining an array of ultrasonic time signals of size LN, each coefficient K.sub.i,j(t) of this array representing the measurement signal received by the j-th reception transducer due to the i-th emission; and denoising the time signal array by removing some of the singular values and associated singular vectors obtained from a singular value decomposition of a frequency signal array obtained by transforming this time signal array, and by reconstructing a denoised time signal array based on unremoved singular values and singular vectors.

The disclosure relates to methods, systems, and apparatuses for virtual sensor data generation and more particularly relates to generation of virtual sensor data for training and testing models or algorithms to detect objects or obstacles. A method for generating virtual sensor data includes simulating, using one or more processors, a three-dimensional (3D) environment comprising one or more virtual objects. The method includes generating, using one or more processors, virtual sensor data for a plurality of positions of one or more sensors within the 3D environment. The method includes determining, using one or more processors, virtual ground truth corresponding to each of the plurality of positions, wherein the ground truth comprises a dimension or parameter of the one or more virtual objects. The method includes storing and associating the virtual sensor data and the virtual ground truth using one or more processors.

The disclosure relates to methods, systems, and apparatuses for virtual sensor data generation and more particularly relates to generation of virtual sensor data for training and testing models or algorithms to detect objects or obstacles, such as wheel stops or parking barriers. A method for generating virtual sensor data includes simulating a three-dimensional (3D) environment comprising one or more objects. The method includes generating virtual sensor data for a plurality of positions of one or more sensors within the 3D environment. The method includes determining virtual ground truth corresponding to each of the plurality of positions, wherein the ground truth includes information about at least one object within the virtual sensor data. The method also includes storing and associating the virtual sensor data and the virtual ground truth.

The disclosure relates to methods, systems, and apparatuses for virtual sensor data generation and more particularly relates to generation of virtual sensor data for training and testing models or algorithms to detect objects or obstacles, such as wheel stops or parking barriers. A method for generating virtual sensor data includes simulating a three-dimensional (3D) environment comprising one or more objects. The method includes generating virtual sensor data for a plurality of positions of one or more sensors within the 3D environment. The method includes determining virtual ground truth corresponding to each of the plurality of positions, wherein the ground truth includes information about at least one object within the virtual sensor data. The method also includes storing and associating the virtual sensor data and the virtual ground truth.