23 results about "Sonar signal processing" patented technology

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 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 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 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 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.

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 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 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.

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.

The present application relates to the technical field of sonar signal processing, and in particular to a passive multi-beam narrowband detection method under the influence of near-field suppression type strong interference, which realizes the estimation of the distance and azimuth of strong interference by multi-scale focusing distance scanning and conventional beam forming with low computational complexity, thereby realizing the correction of the near-field model; in combination with a tolerant interference suppression method, the strong interference can be effectively suppressed by using the corrected focusing steering vector, and the present application can well suppress the influence of near-field strong interference and effectively improve the narrowband target detection performance of passive sonar in a near-field strong interference environment.

The present application relates to the technical field of sonar signal processing, and particularly relates to a passive target detection distance evaluation method under strong interference based on difference characteristics. The method is used for evaluating the influence of strong interference on targets. In a traditional sonar equation, an interference level, an interference suppression gain and a feature detection threshold are introduced to quantize the influence of strong interference on passive sonar prediction distance. Firstly, a propagation loss curve is calculated according to hydrological conditions. Then, the interference level, the interference suppression gain, the interference propagation loss, the feature detection index obtained by a multi-dimensional feature joint detection method and the feature detection threshold are calculated according to the set parameters of the strong interference and the target. The traditional passive sonar equation is optimized to obtain an optimized quality factor. In combination with the propagation loss curve, a corrected passive sonar prediction distance is obtained.

The present application relates to the technical field of sonar signal processing, and particularly relates to a smoothing filtering method based on multi-beam narrow-band warning line integration, which comprises the following steps: (1) obtaining multi-beam narrow-band data; (2) pre-processing the obtained multi-beam narrow-band data, and supplementing data values of a half-beam size before and after the data; (3) converting the multi-beam narrow-band data into projection data through line integration transformation, and performing filtering processing on the projection data in the projection domain; and (4) back-projecting the filtered projection data to obtain reconstructed narrow-band data. After the line integration smoothing filtering of the multi-beam narrow-band data, high-resolution spatial energy spectrum can be obtained.

The invention belongs to the field of sonar signal processing, and particularly relates to a method for suppressing pile-driving sonar signals based on a deep-sea horizontal array. The method comprises the following steps: a first step of obtaining an azimuth history diagram of the deep-sea horizontal array; a second step of calculating the background noise of each element in a column vector extracted at any azimuth of the deep-sea horizontal array azimuth history diagram; a third step of comparing the column vector extracted in the second step with the calculated background noise of the element element by element, to obtain a set of new column vectors; a fourth step of traversing all azimuths in the second step to obtain a new azimuth history diagram; a fifth step of performing point-by-point subtraction and modulo-taking on the azimuth history diagram obtained in the fourth step, to output a azimuth history diagram for ultimately suppressing the pile-driving sonar signal. The method proposed by the invention directly suppresses the pile-driving sonar signal on the azimuth history diagram, and does not have the problem of filtering out targets as may occur in a frequency domain filtering method.

The invention provides a mixed norm time domain broadband beam forming method under a planar array projection coordinate system, which belongs to the technical field of sonar signal processing, and comprises the following steps: calculating the expected frequency response of a finite impulse response filter according to a conventional beam forming weight, and carrying out pre-delay processing on a received signal to obtain a mixed norm time domain broadband beam; a mixed norm constraint criterion is adopted to carry out two-norm constraint on a pass band and infinite norm constraint on a stop band, a finite impulse response filter optimization target and constraint conditions are established, a convex optimization solver is utilized to solve a time domain impulse response of a finite impulse response filter, and after a received echo signal passes through the finite impulse response filter, the finite impulse response is obtained. The problems that when array element time delay is calculated in planar array broadband beam forming, due to the fact that a spherical coordinate system is adopted, an azimuth angle and a pitch angle are in a product relation, time delay calculation complexity is high, and beam forming performance is reduced due to the fact that constraints of a pass band and a stop band are unbalanced in the design of a filter are solved.

The invention relates to the technical field of underwater acoustic engineering, sonar signal processing and harmonic detection, in particular to an interference equipment identification method based on forwarding harmonic characteristics, which comprises the following steps of: firstly, carrying out matched filtering and sampling on an obtained active sonar echo signal, and then extracting a corresponding cepstrum by using a cepstrum algorithm; and finally, performing non-direct-current component detection on the obtained cepstrum, and judging whether the target is an interference device or not according to the ratio of the non-direct-current component to noise energy. According to the method, a forwarding mechanism of an underwater decoy target is utilized, harmonic signal characteristics of the underwater decoy target are shown through matched filtering, and on the basis, the underwater decoy target is identified and eliminated by means of harmonic signal identification. According to the method, the identification capability of interference equipment is effectively improved, the algorithm process is simple, the calculation complexity is low, the portability is high, and an important component module is provided for constructing a detection and identification system of an underwater target.