66 results about "Signal modeling" patented technology

The invention discloses a power coupling-considered capacity ratio estimation method for a network-constructing / network-following multi-machine hybrid system, and the method comprises the steps: building a GFL-GFM hybrid system model, combining VSG power coupling small signal modeling and a dynamic relative gain matrix (DRGA), and quantifying the coupling strength of active / reactive power to output voltage; the frequency domain impedance characteristic of the GFM converter is simplified, and an ideal voltage source series equivalent reactance equivalent model is constructed; deriving an analytical relationship between a generalized short-circuit ratio (gSCR) and a capacity ratio based on the model, and generating a ratio formula in combination with engineering boundary sub-scenes to form a ratio range suitable for multiple scenes; for coupling time-varying characteristics, a closed-loop mechanism of'mixed mode-coupling sensing-correction calculation-execution feedback 'is constructed, and the ratio is dynamically adjusted. According to the method, coupling quantization and multi-machine coordination control are deeply fused, the problem that the external characteristic model precision and the multi-working-condition adaptability are difficult to consider under complex environment coupling is effectively solved, and the engineering applicability of the hybrid fan system is enhanced.

The invention discloses an RIS-assisted millimeter wave satellite communication system channel estimation method based on PARAFAC. The method comprises the following steps: constructing an RIS-assisted millimeter wave satellite communication system cascade channel model; the method comprises the following steps: modeling received signals of an RIS-assisted satellite communication system into a third-order parallel factor (PARAFAC) model through data reconstruction based on a multi-dimensional structure of an RIS-assisted millimeter wave satellite communication system channel; and performing parallel factorization on received signals of the RIS-assisted satellite communication system by using an alternating optimization method to obtain an estimated value of a model factor matrix, and finally reconstructing an RIS-assisted satellite communication channel by using the estimated value of the factor matrix to obtain a channel estimated value. The RIS-assisted millimeter wave satellite communication system channel estimation method can accurately achieve RIS-assisted millimeter wave satellite communication system channel estimation, and the performance of the RIS-assisted millimeter wave satellite communication system channel estimation method is superior to that of a traditional least square method (LS)-based channel estimation method.

The invention discloses an enhanced power decoupling control method for a virtual synchronous generator, relates to the technical field of virtual synchronous generators, and solves the problems that a systematic analysis method for a resistance-inductance line power coupling mechanism is lacked and a collaborative design framework of a dynamic power decoupling condition and a steady-state power transmission requirement cannot be established in the prior art. According to the method, firstly, a dynamic coupling coefficient is accurately quantified through small signal modeling, then a voltage amplitude compensation mechanism based on virtual impedance is established, steady-state power transmission constraints are embedded into dynamic decoupling conditions, and virtual impedance parameters have the dual functions of eliminating dynamic coupling and guaranteeing steady-state tracking. The method does not depend on ideal working condition assumption, can calculate the optimal virtual resistance and virtual reactance on line according to real-time line parameters and operation working conditions, improves the adaptability of the VSG to a weak power grid resistance-inductance line, effectively inhibits dynamic cross coupling between power, and enhances the frequency support and voltage support capability of the VSG under a complex power grid condition.

The invention provides a wind power integration system small disturbance modeling and stability analysis method considering control delay, and the method comprises the steps: introducing a sampling delay link, a zero-order holding link and a switch delay link in a small disturbance linearization modeling process, carrying out the linearization processing through employing a first-order inertia link, and building a unified state space model; respectively constructing control delay mathematical models of the direct-driven fan and the double-fed fan, and analyzing and identifying the influence of the control delay on the oscillation mode and stability of the system through characteristic values and impedance; and finally, performing time domain simulation in the simulation platform, and comparing a calculation result with a simulation result to verify the accuracy of the model. The method can accurately reflect the small disturbance characteristics of the wind power grid-connected system in the sub-synchronous frequency band and the super-synchronous frequency band, provides a theoretical basis for optimization of control parameters of a wind turbine generator and evaluation of grid-connected stability, and solves the technical problem that the influence of control delay is generally ignored in modeling of an existing wind power grid-connected system.

This invention proposes an integrated beamforming method and system for communication and sensing based on reconfigurable smart surfaces, belonging to the field of wireless communication technology. The aim is to design suitable beamforming to maximize communication and data rate while ensuring adequate radar sensing performance. The method includes: first, constructing an ISAC system containing J RIS elements, a base station (BS), and M single-antenna mobile users (MUs), and completing the modeling of baseband signals and user received signals; second, constructing user communication and data rate models and radar target detection signal-to-noise ratio models, establishing unit mode constraints on RIS reflection coefficients and transmit power constraints; third, employing an improved algorithm combining alternating optimization and fractional programming to decompose the non-convex optimization problem into sub-problems for iterative solution, ultimately maximizing communication and data rate and radar sensing performance, while also meeting the dual functional requirements of communication and sensing. This invention is applicable to providing target detection and communication functions for vehicles.

The application discloses a non-uniform noise background-based sparse array gridless parameter estimation method, and the implementation steps are as follows: a sparse array structure is arranged at a receiving end; a sparse array receiving signal in a non-uniform noise background is modeled; a covariance matrix of the array receiving signal is calculated; receiving data of a virtual differential common array is calculated through vectorization and de-redundancy; a distribution to which a fitting error is subjected is derived, and a parameter estimation optimization model based on atomic norm minimization and avoiding a complex regularization parameter determination process is constructed; a semi-positive definite programming form of a primal problem and a dual problem is derived; and a wave direction estimation result is obtained through a MUSIC algorithm or polynomial root seeking. In addition, on the basis of fully utilizing a virtual differential common array of the sparse array to provide extended degrees of freedom and all information, the application restrains the influence of non-uniform noise by constraining the sparsity of data atoms to be recovered and selecting a regularization parameter from a chi-square distribution table according to a distribution to which a fitting error between the data to be recovered and actual receiving data not affected by noise is subjected, overcomes the grid mismatch problem caused by parameter domain discretization, avoids a complex process of determining the regularization parameter, and can obtain a higher-precision source direction estimation result.

The invention provides a distributed radar-oriented low-interception probing integrated signal design method and system, and relates to the field of wireless communication and radars, and the method comprises the steps: obtaining first information and second information; performing distributed node emission signal modeling according to the first information and the second information to obtain a signal expression of each emission node; illegal reconnaissance interception receiving signal modeling is carried out according to the signal expression, and a total signal model received by an interception machine is obtained; performing low interception performance optimization target design according to the total signal model to obtain an optimization target function; constructing a distributed low-interception probing integrated signal design model according to the optimization objective function to obtain a joint optimization problem model; and performing optimization solution according to the joint optimization problem model to obtain a low-interception probing integrated signal. According to the invention, the anti-interception and anti-eavesdropping capabilities of the distributed co-detection system are improved, and balanced optimization of detection, communication and safety performance is realized.

This invention belongs to the field of linear periodic time-varying system modeling and analysis technology, and discloses a small-signal modeling method and application for LCC-HVDC systems. The method includes: constructing mathematical models of the segmented and continuous parts of the LCC-HVDC system based on its circuit topology within each operating interval, and integrating these models as the mathematical model of the LCC-HVDC system; linearizing the trajectory of this mathematical model to obtain its small-signal model within each operating interval; designing a small-signal model of the LCC-HVDC system during switching between adjacent operating intervals using the Filippov method; and combining the small-signal models of the LCC-HVDC system within each operating interval and the small-signal models at the switching time to constitute the small-signal model of the LCC-HVDC system, thus completing the small-signal modeling. This invention can accurately characterize the switching dynamics of the LCC-HVDC system, achieving accurate and low-complexity small-signal modeling of the LCC-HVDC system.

The invention belongs to the technical field of power electronic control and system stability analysis in a new energy power generation system, and discloses a small signal modeling method for a module-level power optimizer. According to the method, a unified small signal model among a photovoltaic module, a DC / DC power converter, an inductor, a capacitor, a load and a controller is established; determining a transfer function relationship among output voltage disturbance, duty ratio disturbance and a control error signal; packaging a single-module model into a standard negative feedback control structure, and supporting Bode and Nyquist stability analysis; the method can be popularized to a multi-module series or parallel system, and system-level small signal stability evaluation is realized.

The invention discloses a microwave transistor small signal modeling method and system, and belongs to the technical field of microwave circuit and device modeling, and the method is based on a Kolmogorov-Arnold network (Kolmogorov-Arnold Network, KAN), and comprises the following steps: firstly, constructing the Kolmogorov-Arnold network and an adjoint network of the Kolmogorov-Arnold network; secondly, building a model training architecture based on small signal S parameter data under direct current and multi-bias conditions; then, training the training architecture by using small signal S parameter data under direct current and multiple biases; and finally, exporting the trained microwave transistor small signal model. According to the method, the novel Kolmogov-Arnod network is introduced to realize small-signal modeling of the microwave transistor, so that the modeling precision and generalization capability are remarkably improved, and an efficient and reliable technical solution is provided for a transistor modeling task in microwave circuit design.

The invention discloses an oil field pipeline intrusion behavior generation type early warning method and system based on radar signal time sequence prediction and a Diffusion model, and relates to the field of oil field security and protection monitoring. The problems that in the field of oil field security and protection monitoring, single-model detection robustness is insufficient, normal signal modeling is not accurate, sample dependence and data scarcity contradictions exist, an anomaly judgment mechanism is rigid, and full-process collaboration is missing are solved, and the method comprises the steps that synthetic data and real data are generated through a GUI; the generated synthetic data and the real data are preprocessed; constructing an LSTM (Long Short Term Memory) time sequence prediction model and a Diffusion model, and carrying out standardization processing; a weighted summation strategy is adopted to calculate a comprehensive abnormal score, a self-adaptive abnormal threshold value is set, and when the comprehensive abnormal score exceeds the threshold value, it is judged that an intrusion behavior exists, and early warning is triggered; and naming and storing an intrusion behavior detection result according to a timestamp, so as to support historical data query and statistical analysis and complete oilfield pipeline intrusion behavior generation type early warning.

The present application relates to a kind of myelin repair auxiliary method based on neural signal modeling.The method obtains the multi-modal neural signal data such as electroencephalogram signal of individual to be rehabilitated and is preprocessed, forms preprocessed data set;Subsequently, individualized time series modeling process is executed, and the time series characteristic representation including nerve conduction velocity recovery rate, phase consistency and neural pathway integrity is generated, and individualized calibration is carried out by dynamic baseline updating mechanism.The calibrated feature representation is input to the pre-trained deep learning inference engine.The inference engine outputs myelin repair index and imbalance risk score, which is used to represent the degree of repair and predict future abnormal risk.Based on the above index, a set of intervention parameters is generated, including electrical stimulation intervention parameters, virtual rehabilitation training task difficulty and rehabilitation training rhythm, and further forming control instructions to configure virtual rehabilitation training environment and electrical stimulation execution interface, so as to realize the individualized assistance and dynamic optimization of myelin regeneration repair.

The invention, which relates to the technical field of the thermal power plant intelligent inspection robot, discloses a thermal power plant intelligent inspection robot system based on a 5G private network, comprising an inspection robot module, a signal modeling module, a path planning module, a communication monitoring module, an AI regulation and control module, a slice management module and an edge decision module. The inspection robot module is used for executing an inspection task in a thermal power plant, collecting equipment state data and uploading the equipment state data through a 5G private network; the signal modeling module is used for constructing a 5G signal intensity spatial distribution model in the factory based on the reference signal receiving power reported by the inspection robot module and the factory space structure information; by constructing a 5G signal intensity space distribution model and introducing the model into path planning, collaborative optimization of physical reachability and communication reliability of a routing inspection path is realized, the problem of communication interruption caused by metal shielding in traditional routing inspection is effectively avoided, and a communication effectiveness index output in real time by a communication monitoring module is combined.

The application provides a single-loop PI parameter design method and system based on a two-line DC power flow controller, comprising the following steps: step 1: performing working condition analysis on a two-line common inductance type DC power flow controller, including transient operation analysis on the common inductance and the capacitor; step 2: small signal modeling of the two-line common inductance type DC power flow controller; step 3: building a simplified transfer function block diagram through a state space equation, and then calculating a PI parameter expression through the gain of an open-loop transfer function, and obtaining the designed PI parameter through the selection of a control bandwidth. The application comprehensively considers the control bandwidth of a control loop and the phase margin actual demand of the two-line DC power flow controller, designs the single-loop PI parameter of the two-line common inductance type DC power flow controller, and realizes the optimal phase margin and stability.

The invention discloses a method and a system for suppressing low-frequency oscillation of a network construction type energy storage converter, and belongs to the technical field of energy storage, and the method comprises the following steps: constructing a small-signal impedance model of the network construction type energy storage converter based on virtual admittance control by using a small-signal modeling method; order reduction simplification is carried out on the impedance model, key characteristics of a 0.1-10Hz synchronous frequency band are reserved, and oscillation core inducements in a current steady-state value matrix are identified; and adding a q-axis voltage feedforward control link, introducing a regulation coefficient, and modifying the regulation coefficient to enable the modified regulation coefficient to be negative to counteract oscillation inducements. The method can effectively suppress the interactive oscillation of the grid-forming type energy storage converter and the power grid at the low frequency band, improves the system stability, is suitable for various operation conditions, and has important engineering application value.

The present application relates to LLC resonant converter technical field, specifically to a kind of LLC resonant converter small signal modeling method based on time domain correction;Mainly include the following steps: establishing the equivalent model of LLC resonant converter each element and third-order average value equivalent circuit, LLC resonant converter small signal modeling method is reduced to second-order equivalent circuit by third-order average value equivalent circuit, add disturbance in second-order equivalent circuit, and separate large signal component and second-order small signal disturbance to obtain the analytical form of second-order average value small signal model;The LLC resonant converter small signal modeling method proposed in the scheme considers high precision and ease of use, improves the applicable frequency range, can guide LLC resonant converter controller design and stability analysis, the average value small signal model established by time domain analysis has higher precision, and analytical form transfer function is given, to facilitate practical engineering application.

The application relates to a DNN-based large-signal model modeling method, system, device and storage medium, and relates to the technical field of integrated circuits. The method is based on a GaN microwave device including a GaN transistor. The method comprises the following steps: performing large-signal testing on the GaN transistor to obtain a traveling wave characteristic; processing input layer characteristics and output layer characteristics in the traveling wave characteristic to obtain input layer data and output layer data; extracting real part and imaginary part data and training a high-power area deep neural network model by using a DNN; extracting amplitude and phase data and training a low-power area deep neural network model by using a DNN; training the traveling wave characteristic according to the high-power area deep neural network model and the low-power area deep neural network model to obtain a trained traveling wave characteristic, and converting the trained traveling wave characteristic into a voltage-current characteristic; and constructing a large-signal behavior model according to the voltage-current characteristic. The application has the technical effect of improving the accuracy of a large-signal modeling model of a GaN microwave device.

The present application relates to a kind of power plant air supply fan fault diagnosis method, system and electronic equipment.The present application is first to the original vibration signal of nonlinear non-stationary initial noise reduction, remove part of random particle noise;Second, by latent factor model (Latent Factor Model, LFM), signal modeling is obtained to hidden feature, and signal decomposition is carried out to the noise reduction signal, realizes secondary noise reduction;Finally, based on the extracted product function (Product Function, PF) component (i.e. second PF component), using the efficient scalable multi-fault classifier obtains the diagnosis result, and then efficiently and accurately realizes power plant air supply fan fault diagnosis.

The present application relates to a kind of unmanned plane communication perception integrated system beam forming and resource scheduling method, belong to wireless communication technical field.The method includes: modeling unmanned plane communication perception integrated system model;Modeling unmanned plane communication channel model;Modeling unmanned plane communication signal;Modeling user communication rate and communication time;Modeling target perception resolution and perception correlation variable;Modeling unmanned plane signal power constraint and flight energy consumption;Modeling unmanned plane resource scheduling and flight trajectory constraint;Based on system performance optimization determines unmanned plane beam forming, correlation strategy and flight trajectory.The present application minimizes communication time, maximizes correlation coefficient and minimizes unmanned plane flight energy consumption as optimization goal, realizes the joint optimization of unmanned plane beam forming, correlation strategy and flight trajectory.

The application discloses a kind of based on multi-dimensional signal feature mapping method and device of double branch structure, belong to artificial intelligence and multi-dimensional signal processing technical field.Method includes following steps: to multi-dimensional input signal is preprocessed, the preprocessing includes normalization, feature alignment and numerical domain adaptation;Local mode is extracted by local mode extraction branch input signal local mode feature, and output local feature vector;By base function feature enhancement branch, input signal is carried out nonlinear feature enhancement, and output high nonlinear feature vector;Local feature vector and high nonlinear feature vector are adaptively fused, and generate fusion feature vector;Fusion feature vector is carried out nonlinear mapping, and output prediction or classification result.The application is through double branch complementary structure and adaptive fusion mechanism, while guaranteeing the calculation efficiency, the precision of multi-source signal modeling and prediction is improved, overcomes the problem of insufficient feature extraction and insufficient nonlinear expression ability in prior art.

The invention discloses a distributed coherent aperture radar angle ambiguity resolution method based on maximum likelihood estimation in the technical field of radar signal processing. Aiming at the problem of angle ambiguity of the distributed coherent aperture radar caused by transmitting beam grating lobes, the method comprises the following steps: firstly, transmitting a group of carrier frequency linear stepping pulse sequences; then carrying out beam forming on received echoes, and carrying out coherent accumulation on beam output of a plurality of pulses by utilizing the characteristic that main lobe response does not deviate along with the frequency and grating lobe response deviates along with the frequency, so as to suppress grating lobes and enhance the main lobe on the aspect of energy; and finally, modeling is carried out on the accumulated signals, and unambiguous angle estimation is realized by solving a conditional maximum likelihood estimator of a target direction. The method can effectively solve the problem of angle measurement ambiguity caused by transmitting grating lobes under the condition that the beam coverage range is not lost, and particularly has the advantages of high precision and high robustness in a low signal-to-noise ratio environment.

The embodiment of the invention relates to a droop control inverter sequence impedance modeling method and system and a server, and the modeling method comprises the steps: adding positive sequence small signal current disturbance with a preset frequency at a grid connection point between a droop control inverter and a power grid, and carrying out the modeling of a small signal in a current disturbance influence process, and then considering the influence of each control link and frequency coupling on the alternating current side impedance of the droop control inverter, so that a more accurate model can be established, and the modeling process is simple and convenient and easy to realize. According to the modeling method, the influence of each control link and the main circuit parameters on the stability of the inverter can be clearly known, and harmonic oscillation can be avoided by adjusting the main circuit and the control parameters of the droop control inverter.

The application discloses a kind of sparse array amplitude-phase error correction-based meshless parameter estimation method, and its implementation steps are: receiving end is laid out sparse array;The received signal of sparse array with array element gain phase error is modeled;Sample covariance matrix is constructed;The output signal of virtual differential common array is calculated by vectorization;Define the atom norm of introducing amplitude-phase error parameter, and construct the optimization model for target direction estimation;By dual atom norm, the original optimization problem is converted into its dual problem;The semi-positive definite programming form of dual problem is deduced;Dual polynomial is constructed, and the wave direction estimation result is obtained by spectral peak search.In addition, the application fully utilizes the virtual differential common array of sparse array to provide extended degrees of freedom and all information, and suppresses the influence of array element amplitude-phase error by defining new atom norm, solves the mesh mismatch problem caused by parameter domain discretization, and obtains high-precision meshless direction estimation result.

The invention discloses a bistatic multi-channel synthetic aperture radar (SAR) synchronous signal extraction method and device, and belongs to the technical field of synthetic aperture radar signal processing. According to the method, a bistatic SAR system with a plurality of receiving channels is constructed, and a synchronization signal and a scene echo signal are modeled into a linear mixed signal by using time delay and amplitude differences caused by physical position differences among the channels; a blind source separation algorithm based on high-order statistics is adopted to carry out centralization, whitening and joint diagonalization processing on multichannel received signals, and effective separation of synchronous signals and target echoes is realized. The method does not need to interrupt the imaging process, does not depend on priori knowledge or complex waveform design, remarkably improves the phase synchronization precision and the system flexibility, is suitable for various bistatic SAR systems, and has good practicability and universality.

The application discloses a wide-frequency scattering source cooperative positioning system based on an underwater sensor network, relates to the technical field of underwater sensor network positioning, and comprises the following parts: a distributed underwater sensor node group, which is arranged in an underwater monitoring area and cooperatively collects underwater acoustic signals of a wide-frequency scattering source; a parameter initialization configuration module; an air-frequency domain joint signal modeling module; a cooperative reconstruction base construction module; a sampling signal preprocessing module; a low-rank constraint optimization solving module; and a scattering source parameter solving module, which is used for solving positioning parameters of the wide-frequency scattering source according to a solved air-frequency joint distribution density matrix. The application effectively corrects the attenuation difference of the wide-frequency signal, improves the quality of the signal, and further improves the positioning precision. Through dynamic node position calibration and dynamic adjustment of the calibration period according to the ocean current velocity, the movement of the node can be effectively tracked, the real-time performance of the node position is ensured, and the positioning error caused by the movement of the node is avoided.

The invention discloses a novel polypeptide synthesizer, which relates to the technical field of polypeptide synthesis, and comprises a ternary cooperative signal modeling module, a bubble time sequence analysis module, a photoacoustic coupling compensation module, a bubble discharge and circulation control module, a dynamic stability adjustment module and a self-correction optical path shaping module, establishing a ternary collaborative baseline of an ultraviolet detection signal, a pressure detection signal and a flow detection signal, reconstructing a flow cell optical path distribution model, extracting optical path refraction fingerprints, and forming a gas-liquid interface coupled dynamic monitoring reference system. The method is oriented to the field of biological medicine manufacturing, bubble recognition, flow path purification and optical path self-correction are achieved through the photoacoustic coupling detection and phase conjugate optical path shaping technology, a closed-loop control system with memory and feedback functions is constructed, and the accuracy, stability and automation level of the polypeptide synthesis process are remarkably improved.

A system for estimating a vector value of variables of an optimization function, the function comprising a weighted sum of interactions between the variables; the system comprising a plurality of parallel hardware channels, each parallel hardware channel being arranged to model a contribution of a respective variable pair function, each channel comprising: a signal generator configured to generate a signal modeling a value of a respective variable; a splitter arranged to provide the signal to each channel; interaction logic configured to multiply the signal vector by a weight vector modeling an interaction between the respective variable and a vector of variables, thereby generating a feedback signal representing the contribution of the respective variable; and a feedback path for returning the feedback signal to the signal generator, the signal generator being configured to adjust the signal in dependence on the feedback signal, wherein each channel is implemented using only optical and / or analog electronic components.

The application discloses a method for anti-clutter of airborne radar, which comprises the following steps: firstly, modeling the pulse-amplitude-phase time sequence hopping signal, establishing the airborne radar echo model, constructing the pulse-amplitude-phase agile waveform and the joint design of the anti-clutter optimization problem model of the receiving filter bank, and finally, quickly solving the pulse-amplitude-phase agile waveform and the receiving filter bank to realize the robust detection of multiple targets in the clutter background. The method can break through the technical bottleneck that the existing low PRF and medium-high PRF cannot simultaneously consider the range ambiguity and velocity ambiguity by modulating the pulse-amplitude-phase time sequence hopping signal, and based on the block coordinate descent and the efficient optimization method of quadratic transformation, the pulse-amplitude-phase agile waveform and the receiving filter bank are jointly designed to realize the robust detection of multiple targets in the clutter background. Compared with the existing pulse-amplitude-phase agile waveform technology, the method can realize the suppression of the range-velocity clutter and has the multiple target detection capability.

The invention provides a multifunctional signal modeling method, system and device and a medium, and the method comprises the steps: generating binary keying information according to the function type of input data, and configuring a weighted score Fourier transform parameter for the function type according to the binary keying information; performing weighted fractional Fourier transform on the function type to obtain a frequency domain signal parameter; constructing a weighted information cross entropy objective function, performing global optimization on the frequency domain signal parameter according to the weighted information cross entropy objective function, and generating and transmitting a mixed carrier signal; and performing inverse weighted fractional Fourier transform on the mixed carrier signal according to the frame type of the mixed carrier signal to obtain a multifunctional signal. According to the method, a flexible hybrid carrier modulation framework, namely weighted fractional Fourier transform, and weighted information cross entropy are adopted, and weighted fractional Fourier transform parameters are properly adjusted through global optimization, so that deep collaboration and performance compromise of communication, sensing and interference performance are realized.

This invention relates to a bistatic seabed acoustic imaging method based on pixel statistical distribution weighting. Utilizing the characteristic that the positions of real seabed features in the imaging image are fixed while spurious features vary with the position of the receiving array, a statistical method is used to obtain the pixel distribution characteristics of the acoustic image. The statistical distribution probability of each pixel is then used as the pixel weight to perform weighted stitching of multiple acoustic images. The method includes: bistatic seabed scattering signal modeling and simulation, received signal acoustic imaging processing, pixel statistical distribution processing, and weighted stitching and fusion of multiple acoustic images. Compared with conventional bistatic acoustic imaging methods, the method proposed in this invention can effectively reduce spurious features and random noise caused by the inherent characteristics of the one-dimensional horizontal linear array in the acoustic image, highlighting real features in the acoustic image and achieving imaging and discrimination of significant seabed features.