40 results about "Sonar signal processing" patented technology

The invention discloses an intelligent construction site safety management platform and a method thereof. The management platform comprises a data acquisition module, a data processing module, a machine learning prediction module, an intelligent sonar analysis module, an early warning module, a display and notification module and a feedback and learning module. The machine learning prediction module comprises a dynamic feature selection unit, a multi-model integration unit, a context awareness reasoning unit, a self-learning and model updating unit and an uncertainty evaluation unit; the intelligent sonar analysis module comprises a multi-frequency sonar signal processing unit, an environment perception and compensation unit, a target identification and classification unit, a dynamic signal enhancement and noise reduction unit, a real-time position tracking and trajectory prediction unit and a self-learning and system optimization unit. According to the invention, an early warning signal can be rapidly and accurately sent out in a high-risk environment, in addition, an early warning decision value can be adjusted in real time, a potential dangerous situation can be rapidly responded, and the safety risk on a construction site is effectively reduced.

The invention discloses an image sonar gain adaptive control method based on an FPGA. The method comprises the following steps: an upper computer sends a control message carrying a manual gain parameter to a sonar signal processing board based on an Ethernet UDP protocol so as to execute manual gain control; a codeword gain and voltage gain cooperative control architecture is provided; pID closed-loop feedback control is carried out based on beam pattern characteristics, and when a manual gain value changing message issued by the Ethernet is received, the adaptive gain compensation value and the PID historical state are cleared, and the manual gain code is switched to an instruction specified value. According to the invention, conflict-free switching between a self-adaptive mode and a manual mode can be realized, and in addition, the quality of sonar images and the stability of gain regulation and control are improved while large dynamic range and high-precision adjustment of time-varying gain are realized.

The invention belongs to the field of sonar signal processing, and provides an underwater sonar multi-harmonic micro-Doppler feature recognition technology based on CAMobileNetV2. According to the technology, a micro-motion echo model of propeller blades of an underwater vehicle is established, and micro-Doppler characteristics of blades of different numbers and blades of different rotating speeds are obtained by adopting a multi-harmonic signal combined transmitting signal form and utilizing a time-frequency analysis method. In order to more accurately identify and perceive propellers of different types, the invention constructs a CAMobileNetV2 model which is combined with a CBAM (Convolutional Block Attention Module) and MobileNetV2 (Convolutional Block Attention Module), and the CAMobileNetV2 (Convolutional Block Attention Module) model is used for identifying and perceiving propellers of different types. The model can effectively analyze and extract the micro-Doppler characteristics of the propeller, thereby realizing identification of different underwater vehicles. The constructed data set is trained and tested, and the effectiveness and robustness of the technology in underwater sonar signal processing and underwater target identification are shown. The invention provides a micro-Doppler feature recognition technology in the field of underwater sonar signal processing, and is beneficial to improving the target recognition capability of underwater sonar.

The present invention relates to a sonar real-time signal processing method based on GPU. The processing method significantly improves the real-time sonar signal processing efficiency through the high bandwidth, dynamic resource allocation and task optimization of GPU, and includes the following steps: data acquisition and transmission, CPU control scheduling and memory management, GPU operation and processing, data storage and uploading; in the parallel operation process, the GPU implements the task allocation through threads, including beamforming threads, matched filter processing threads, target detection and tracking processing threads and display control interaction threads, so the system will create corresponding threads, and when there are related tasks, the CPU will start the corresponding threads and mobilize the GPU to process. The sonar real-time signal processing method of the present invention effectively breaks through the limitations of real-time and complexity based on the processing architecture of GPU, can realize real-time data processing under high sampling rate conditions, and has significant advantages in sonar real-time signal processing.

The invention relates to the field of sonar signal processing, and provides an unmanned ship multi-beam sonar detection method, system, device, product and medium, and the method comprises the steps: obtaining a side-scan sonar and a multi-beam sonar, scanning the submarine topography through the side-scan sonar and the multi-beam sonar, and obtaining a multi-beam scanning signal and a side scanning signal; performing Kalman filtering to obtain a first filtering signal, and filtering the first filtering signal through an adaptive filtering threshold to obtain a second filtering signal; constructing a minimization energy function, obtaining an optimized filtering signal through the minimization energy function, and carrying out the iteration of the optimized filtering signal, and obtaining a first terrain signal; constructing a generative adversarial network by using a generator and a discriminator, and performing terrain reconstruction on the first terrain signal through the generative adversarial network to obtain a second terrain signal; and correcting the second topographic signal through sound velocity measurement equipment to obtain a target topographic signal, and constructing an underwater topographic scanning graph according to the target topographic signal.

The invention belongs to the technical field of signal and information processing, relates to a modal time delay compensation continuous sound signal target depth estimation method based on a linear array, and is suitable for sonar signal processing. According to the method, on the basis of F-K transformation, through fitting of a sound velocity profile, compensation of modal time delay of each order of each array element, separation of modal of each order in an array receiving signal and a frequency-wavenumber domain, and design of a theoretical curve binary mask filter, modal energy of each order is extracted to be matched with a search depth; and depth estimation of a continuous sound signal target under a general sound velocity profile condition is realized. According to the invention, the depth estimation of a continuous sound signal target is realized, and the problems that a vertical array is difficult to maintain in engineering practice, modal aliasing exists in a continuous signal time-frequency domain by a single hydrophone, and the depth estimation precision error of a depth estimation method under a general sound velocity profile condition is large are solved.

The invention relates to the technical field of image sonar signal processing, in particular to an image sonar arc array wave beam digital correction method. The image sonar signal arc array beam directivity correction method is achieved through a digital method, numerical compensation is carried out on IQ orthogonal signals of all elements of an arc array, beam directivity errors caused by sound velocity changes during beam forming operation are reduced, the method has certain universality, and the method is suitable for popularization and application. The method is especially suitable for the field of small high-frequency image sonar signal processing, and can effectively relieve the difficulty of correcting the orientation precision in the later period. Meanwhile, the correction method adopted by the invention is simple and effective, can be realized by using hardware with limited resources, and is high in portability; according to the design method, the influence of the sound velocity change on the arc array beam directivity is effectively reduced, so that the image sonar orientation error caused by the sound velocity change is reduced.

The present invention relates to a method for improving the target resolution of a fishing sonar image, belonging to the technical field of fishing sonar. The method for improving the target resolution of a fishing sonar image includes the following steps: obtaining the echo data uploaded by the sonar signal processing host, and preprocessing the data to obtain preprocessed echo data data; performing interpolation visualization imaging on the preprocessed echo data data to obtain an initial fishing sonar image; introducing a gain Gain to adjust the echo intensity value of the initial fishing sonar image to obtain an adjusted echo intensity value Image data of the initial fishing sonar image; performing interpolation visualization imaging on the adjusted echo intensity value Image data to obtain an adjusted fishing sonar image. The method for improving the target resolution of a fishing sonar image provided by the present invention adjusts the display of the fishing sonar image target by introducing a gain Gain to adjust the echo intensity value of the initial fishing sonar image so as to make up for the loss of the echo intensity of the long-distance caused by the hardware of the signal receiver.

The invention relates to the technical field of sonar signal processing, in particular to a difference characteristic-based passive target detection distance evaluation method under strong interference, which specifically evaluates the influence of strong interference on a target, and introduces an interference level, an interference suppression gain and a characteristic detection threshold into a traditional sonar equation. The influence of strong interference on the passive sonar forecast distance is quantified. The method comprises the following steps: firstly, calculating a propagation loss curve according to hydrological conditions, and then calculating an interference level, an interference suppression gain, interference propagation loss, and various parameters such as a feature detection index and a feature detection threshold obtained by a multi-dimensional feature joint detection method according to set parameters of strong interference and a target; and optimizing a traditional passive sonar equation to obtain an optimized high-quality factor, and obtaining a corrected passive sonar forecast distance in combination with the propagation loss curve.

The invention relates to the technical field of sonar signal processing, in particular to a passive multi-beam narrow-band detection method under the influence of near-field suppression type strong interference, which quickly realizes the estimation of strong interference distance and direction through multi-scale focusing distance scanning and relying on conventional beam forming with low computational complexity, thereby realizing the correction of a near-field model; according to the passive sonar narrow-band target detection method, strong interference can be effectively suppressed by combining a tolerance interference suppression method and utilizing a corrected focusing steering vector, the influence of near-field strong interference can be well suppressed, and the passive sonar narrow-band target detection efficiency in a near-field strong interference environment can be effectively improved.

The invention discloses a fluctuating background adaptive estimation method under active sonar multi-clutter strong interference, and belongs to the field of active sonar underwater acoustic signal processing. According to the method, backgrounds are respectively estimated through the left eccentric analysis window and the right eccentric analysis window, then the smaller value is taken as the interference background estimation value near the position of the target, and then the signal-to-interference ratio is calculated, so that the risk that a weak target is masked by neighbor strong interference can be avoided or reduced. The method provided by the invention can be used for estimating the uneven background in active sonar application, in particular to self-adaptive estimation of the uneven background in the presence of multi-clutter strong interference. The signal-to-noise ratio of the target can be directly obtained according to the estimated dynamic background, and a basis is established for target detection and positioning. Adaptive estimation of the fluctuating background under multi-clutter strong interference is a necessary preposed link of active sonar signal processing and has an important footstone position.

The present invention provides a method for measuring the beamforming direction vector during the steering process of a towed array sonar platform, and belongs to the technical field of underwater acoustic detection and sonar signal processing. The present invention establishes an array turning model around a circular arc trajectory, and for large-angle turning and small-angle turning, left turning and right turning conditions, uses the center angle of the circle corresponding to the array position arc to decompose the turning process into five turning stages, gives the time point values ​​of four adjacent moments in the five stages, and for each turning stage, takes the first array element as a reference, gives the beamforming direction vector at the current moment, which has great application value for improving the target azimuth estimation performance during the turning process.

The embodiment of the invention provides a broadband Doppler sonar signal processing method and system, and belongs to the technical field of signals. The method comprises the following steps: receiving echo signals after the broadband Doppler sonar transmits a plurality of pulse signals; performing frequency shift estimation on a single pulse of the echo signal to obtain a frequency shift interval; performing inter-pulse frequency calculation on the echo signal to obtain an average frequency of a single beam channel; performing frequency shift value calculation according to the average frequency and the frequency shift interval to obtain an echo offset value of a single beam channel; and performing speed calculation according to the echo offset values of the plurality of beam channels to obtain the three-dimensional speed of the measured target. According to the embodiment of the invention, the speed measurement precision of the broadband Doppler sonar under the shallow water condition can be improved.

The present application relates to underwater acoustic engineering, sonar signal processing and harmonic detection technical field, especially a kind of jammer equipment identification method based on retransmission harmonic feature, first the active sonar echo signal obtained is carried out matching filtering and sampling, then using cepstrum algorithm to extract its corresponding cepstrum, finally the obtained cepstrum is detected without direct current component, whether the target is jammer equipment is judged by the ratio of non-direct current component and noise energy.The present application utilizes the retransmission mechanism of underwater decoy target, exposes its harmonic signal characteristics through matching filtering, and on this basis, relies on harmonic signal identification means to identify and eliminate it.The present application effectively improves the identification ability of jammer equipment, and the algorithm process is simple, the calculation complexity is low, the portability is strong, provides an important component module for constructing the detection and identification system of underwater target.

The present application relates to the technical field of sonar signal processing, and in particular to a passive distributed joint detection method of spatial windowing and unwrapping, which is a sonar passive distributed joint detection method of one-dimensional azimuth space energy spectrum, and is used for passive target positioning, and the present application does not need prior information such as target sound source level and detection threshold, and can effectively eliminate false peak points of cross positioning.

This invention belongs to the field of sonar signal processing and proposes an underwater sonar multi-harmonic micro-Doppler feature recognition technology based on CAMobileNetV2. This technology establishes a micro-echo model of underwater vehicle propeller blades, employs a combined multi-harmonic signal transmission signal, and utilizes time-frequency analysis methods to obtain the micro-Doppler features of blades with different numbers and rotational speeds. To more accurately identify and perceive different types of propellers, this invention constructs a CAMobileNetV2 model combining CBAM (Convolutional Block Attention Module) and MobileNetV2. This model can effectively analyze and extract the micro-Doppler features of the propeller, thereby achieving the identification of different underwater vehicles. Training and testing on the constructed dataset demonstrate the effectiveness and robustness of this technology in underwater sonar signal processing and underwater target recognition. This invention provides a micro-Doppler feature recognition technique in the field of underwater sonar signal processing, which is beneficial for improving the target recognition capability of underwater sonar.

The invention belongs to the technical field of signal and information processing, relates to a common sound velocity profile target depth estimation method based on frequency dispersion elimination transformation, and is suitable for sonar signal processing. In order to overcome the influence of parameter estimation precision reduction caused by sound velocity profile change, on the basis of traditional frequency dispersion elimination transformation, depth estimation under a general sound velocity profile condition is realized by optimizing global waveguide invariants, fitting a sound velocity profile, calculating an equivalent propagation distance and redesigning a frequency dispersion elimination kernel function and an energy matching function.

The invention discloses a method for developing sonar signal processing software based on QT and MATLAB hybrid programming, which comprises the following steps of: (1) algorithm implementation: compiling codes of an algorithm part through MATLAB to generate a MATLAB file 'cbf.m'; (2) generating a dynamic link library: creating a C + + dynamic link library through a Library Compiler tool; (3) calling a dynamic link library: calling an MATLAB dynamic link library part in the QT; (4) module construction: realizing the function of a single module through a multi-thread mode; and (5) module integration: distributing an independent process for each module to realize parallel processing of each module. According to the method, MATLAB and QT software are combined, signal processing software is divided into an algorithm implementation part and a module integration part, signal processing research work and engineering implementation can be effectively combined together, the real-time performance of system software is improved, development cost is reduced, and meanwhile development efficiency is improved.

The invention relates to the technical field of sonar signal processing, in particular to a smooth filtering method based on multi-beam narrowband warning line integration, which comprises the following steps of: (1) acquiring multi-beam narrowband data; (2) pre-processing the acquired multi-beam narrowband data, and supplementing a data value of a half-beam size before and after the data; (3) converting the multi-beam narrowband data into projection data through line integral transformation, and filtering the projection data in a projection domain; and (4) carrying out back projection on the filtered projection data to obtain reconstructed narrowband data, and carrying out linear integral smooth filtering on the multi-beam narrowband data to obtain a high-resolution space energy spectrum.

The invention discloses a mixed subspace adaptive Riemannian gradient descent target detection method, and belongs to the technical field of underwater sonar signal processing and intelligent sensing. The method comprises the following steps: firstly, constructing a mixed low-rank subspace and heterovariance noise model, and modeling a background into a union set of a plurality of subspaces; then, calculating the posterior responsibility degree of observation data belonging to each subspace mode by using a soft distribution mechanism of temperature control; thirdly, based on a noise variance contour of online learning, a sparse foreground signal is accurately recovered by adopting a weighted soft threshold operator; and finally, introducing an adaptive gain control strategy, updating the subspace basis matrix on line through Riemannian gradient descent, and dynamically adjusting noise parameters. The method has the advantages of being high in heterovariance noise robustness, capable of automatically adapting to abrupt change of the background environment, high in detection precision and the like, and is suitable for real-time detection and tracking of underwater sonar small targets.

Sonar systems and related methods are provided. A sonar system for generating one or more sonar images includes first and second transducer elements each having at least one emitting face. The sonar system also includes a sonar signal processor in electronic communication with the first and second transducer elements to cause transmission of signals from the first and second transducer elements to cause at least one first acoustic beam to be emitted from the first emitting face in a first beam direction and at least one second acoustic beam to be emitted from the second emitting face in a second beam direction. The first and second transducer elements are positioned such that a gap is formed therebetween. The gap is configured to facilitate movement of a fluid therein so as to contribute to an emission of sound power in both the first beam direction and the second beam direction.

The invention belongs to the field of sonar signal processing, and discloses a windowed two-dimensional deconvolution multi-beam power spectrum estimation algorithm, the steps of which include precalculating and storing a full set of guidance vectors of each scanning direction (θ, F) according to an array structure and a processing frequency band, namely, a point spread function; performing a windowed Fourier transform using k-point array element time domain data to obtain an n-th batch of array element frequency domain data; performing a windowed beamformer processing using a pre-stored guidance vector set to obtain a multi-beam power spectrum estimation result; performing a two-dimensional deconvolution processing on a multi-beam power spectrum windowed in a space-time domain using an R-L iterative algorithm in a discrete two-dimensional integral form to estimate the target's real energy distribution estimation PB. out ; After the unwinding process is completed, PB out A two-dimensional spectrum peak search is performed, the minimum value among the extreme points is used as the background estimate, and all non-extreme point backgrounds are smoothed to obtain a new multi-beam power spectrum estimate. The method of the invention effectively improves the performance of passive sonar narrowband warning and has strong engineering practice significance.

The invention discloses detection and identification integrated sonar signal processing hardware equipment based on a mercuric chloride processor and a use method of the detection and identification integrated sonar signal processing hardware equipment. The detection and identification integrated sonar signal processing hardware equipment based on the mercuric chloride processor comprises an intelligent signal processing subsystem and a sonar front-end subsystem, wherein the sonar front-end subsystem comprises a sonar signal transmitting module and a sonar signal acquisition module, and is responsible for responding to a PWM control signal to carry out high-voltage excitation transmission and carrying out high-speed acquisition and transmission on an echo signal in a DMA mode through a PCIe interface; the intelligent signal processing subsystem takes a mercuric chloride AI processor as a core, and is responsible for directly generating an emission control signal, executing beam forming based on a sparse weighting matrix, and identifying a sonar image target based on a dual-network model. According to the invention, the problems of complex hardware link and high external dependence of the traditional architecture are effectively solved, the computing power utilization rate and the integration level of the system are effectively improved, and the system is suitable for being applied to light-weight and intelligent underwater detection equipment in the future.

The application discloses a point cloud data filtering method based on an AI model, and belongs to the technical field of sonar signal processing and point cloud data analysis; first, original sonar data is collected to generate standardized sonar point cloud data; according to the point cloud space density and distribution characteristics, a self-adaptive space block algorithm is used to divide multiple local observation domains; based on the acoustic reflection physical characteristics, a multi-channel linear normalization mapping algorithm is used to real-time render three-dimensional geometric characteristics and acoustic properties into a two-dimensional acoustic feature image; a convolutional neural network with channel and space attention mechanisms is constructed to perform end-to-end detection on the abnormalities in the image; and the detected initial abnormal points are mapped back to the three-dimensional point cloud space; finally, the abnormal probability score of the initial abnormal points is calculated, and the final abnormal points are removed; the application converts acoustic physical properties into visual features, combines a double attention mechanism and two-stage screening, and realizes high-precision and high-efficiency filtering of complex noises such as transducer interference and multipath effects.

The invention belongs to the technical field of underwater robot collision avoidance control, and particularly discloses an underwater robot collision avoidance control method based on multi-sensor data fusion, electronic equipment and a storage medium, and the method comprises the steps: S1, carrying out the preprocessing based on the data obtained by an optical camera and through combining with an image enhancement technology, and obtaining an image data set; s2, processing in a data preprocessing stage based on data acquired by sonar and a sonar signal processing algorithm to obtain a distance data set; s3, based on the data acquired by the pipeline instrument, performing data preprocessing to obtain a pipeline data set; s4, performing data fusion processing according to the obtained image data set, distance data set and pipeline data set; and S5, when it is detected that an obstacle exists in front, intelligent decision making is carried out according to a preset collision avoidance control strategy, and the robot is guided to bypass the obstacle.

The invention discloses a modularly combinable multi-task sonar signal processing system, method and device and a medium, and relates to the technical field of sonar signal processing, the system comprises a data access layer used for selectively receiving sonar data of a multi-source device through a communication interface; and / or optionally calling different types of data reading functions to read off-line data files of the marine environment data; the sonar signal processing algorithm layer comprises a sonar signal processing algorithm library and is used for storing and managing a plurality of standardized underwater acoustic signal processing basic algorithm functions; the underwater acoustic signal processing basic algorithm function is stored, newly added, deleted and / or called in the form of a dynamic library file; and the multi-task module combination layer comprises a multi-task sonar signal processing flow configuration container and is used for visually calling and combining the underwater acoustic signal processing basic algorithm functions so as to build and execute a sonar signal processing task flow in a self-defined manner. The flexibility and the expandability of the sonar signal processing system are improved.

The invention provides a single vector hydrophone DOA dynamic estimation method based on a phase-locked loop, and belongs to the field of sonar signal processing. A single-vector hydrophone DOA open-loop estimation algorithm is used as a phase discriminator, a phase-locked loop is used for dynamically estimating the direction of arrival of a signal, accurate tracking of DOA is kept in a dynamic scene, the problem that a traditional single-vector hydrophone DOA estimation method is not high in precision in the dynamic scene is solved, and the estimation accuracy of the DOA is improved. And outputting an in-phase branch of the phase-locked loop phase discriminator as the optimal synthesis of the vibration velocity. The method is not only small in calculation amount, but also capable of tracking the signal incoming wave direction in real time. And when # imgabs0 # iteratively approaches 0, the in-phase branch of the phase-locked loop phase discriminator is the optimal synthesis of the vibration velocity.

The present application relates to the field of sonar signal processing, and provides an unmanned vehicle multi-beam sonar detection method, system, equipment, product and medium, comprising obtaining a side-scan sonar and a multi-beam sonar, scanning the seabed topography using the side-scan sonar and the multi-beam sonar, obtaining a multi-beam scanning signal and a side-scan signal; performing Kalman filtering to obtain a first filtered signal, filtering the first filtered signal through an adaptive filtering threshold to obtain a second filtered signal; constructing a minimum energy function, obtaining an optimized filtered signal through the minimum energy function and iterating the optimized filtered signal to obtain a first topography signal; constructing a generative adversarial network using a generator and a discriminator, reconstructing the topography of the first topography signal through the generative adversarial network to obtain a second topography signal; correcting the second topography signal through a sound velocity measuring device to obtain a target topography signal, and constructing an underwater topography scanning map according to the target topography signal.

The present invention provides a method for measuring array receiving signals during the steering process of a towed array sonar platform, and belongs to the technical field of underwater acoustic detection and sonar signal processing. The present invention establishes an array steering model around a circular arc trajectory, and for large-angle steering and small-angle steering, left steering and right steering conditions, uses the center angle of the circle corresponding to the array position arc to decompose the steering process into five steering stages, gives the time point values ​​of four adjacent moments in the five stages, and for each steering stage, takes the first array element as a reference, gives the receiving signals of all array elements at the current moment, which has great application value for improving the performance of array signal processing algorithms.

A method for estimating the instantaneous frequency of a moving target based on the phase difference of a frequency line relates to the field of underwater passive sonar signal processing. The present invention is intended to solve the problem of high computational complexity in existing methods for estimating the instantaneous frequency of a moving target. The present invention comprises: performing N-point FFT on the sampled data, and constructing a LOFAR graph according to the time-frequency relationship; using bidirectional α filtering to estimate the power spectrum density Bg(k,j) of the background noise in the LOFAR graph; assigning probability to Bg(k,j) to obtain a trajectory transfer likelihood matrix B; taking a threshold on B to confirm the start and end time of the frequency line, thereby obtaining an existence matrix E; using B and E to search for and track the extreme points on the frequency to obtain a complete frequency line f c ; Extract f c The corresponding phase information is obtained, and the phase difference is obtained, and the phase difference is defuzzified; the phase difference after defuzzification is regressed and analyzed to obtain the instantaneous frequency precise estimation quantity set f e ; Using f e Obtaining the instantaneous frequency set #imgabs0# The present invention is used to estimate the instantaneous frequency of a moving target.