1276 results about "Underwater acoustics" patented technology

The invention discloses an acoustic-optical imaging semantic fusion detection method for underwater defects of a hydraulic structure, and the method comprises the steps: obtaining underwater acoustic and optical images of the hydraulic structure at the same time through underwater acoustic-optical imaging sensing for the underwater defects of the hydraulic structure; and on the basis, acoustic semantic features in the acoustic image are extracted through a semantic feature extraction module, optical image features in the optical image are processed by taking the acoustic semantic features as guidance, and a defect detection result is obtained when an underwater defect target exists in the image, so that underwater defect sound-light imaging semantic fusion detection is realized. The technology is suitable for health monitoring of various dam system hydraulic structures, and operation safety and water safety of hydraulic engineering are guaranteed.

An underwater acoustic sensor network node positioning error correction method combined with acoustic velocity inversion, which method relates to the technical field of acoustic velocity inversion. The method comprises: deploying an acoustic source point and underwater acoustic sensor nodes which are at fixed positions, the underwater acoustic sensor nodes collecting acoustic velocity data sent by means of the acoustic source point, and by means of acoustic velocity data at different underwater acoustic sensor nodes, using an acoustic velocity field inversion algorithm to construct an acoustic velocity field model; collecting real-time acoustic velocity data at the different underwater acoustic sensor nodes, and obtaining acoustic velocity characteristic information at the different underwater acoustic sensor nodes and water characteristic information at the different underwater acoustic sensor nodes; performing comprehensive analysis on the acoustic velocity characteristic information and the water characteristic information, and evaluating the positioning accuracy of the acoustic velocity field model in respect of the underwater acoustic sensor nodes; and comparing quantized positioning accuracy results for the underwater acoustic sensor nodes with a preset threshold, and when there is a relatively large error in the positioning accuracy, generating an error signal. The method is conducive to improving the precision of underwater acoustic wave propagation and the accuracy of underwater acoustic sensor network node positioning, and evaluating the positioning accuracy of an acoustic velocity field model in respect of underwater acoustic sensor nodes.

The invention relates to the technical field of submarine engineering and information processing, in particular to a submarine cable positioning method and system, and the method comprises the steps: synchronously collecting magnetic field, structured light and underwater acoustic signal data, and fusing inertial navigation information to construct a unified space-time reference system; precise registration of heterogeneous data is realized by adopting sliding time window screening, multi-modal noise reduction and rigid body transformation; constructing a graph structure model for expressing cable space-signal features based on the fused data, and reasoning cable path topology by using a graph convolutional network; reconstructing a cable center line through three-dimensional visualization, embedding the cable center line into submarine topography, and realizing risk area dynamic clustering by combining signal integrity score and burial depth estimation; historical time sequence data are fused, a long short-term memory network is adopted to predict cable drift, detectable attenuation and burial depth change trends, risk levels are divided based on prediction results, and spatial distribution early warning and disposal suggestions are output. According to the invention, the cable positioning precision and the risk assessment intelligent level in a complex seabed environment are improved.

Disclosed in the present invention is an underwater acoustic target recognition method based on effective receptive field regulation. A proposed AEU-Net model has a plurality of resolution branches, with each resolution branch having independent convolution kernels, which adaptively adjust their sizes during training while aligning with their respective resolutions. The AEU-Net model comprises an ERF-Server, which can regulate an effective receptive field during forward propagation, and has two operations of increasing or decreasing the effective receptive field of a feature map of any designated module. In the present invention, acoustic physical information of an underwater acoustic target sample can be captured in a plurality of interaction dimensions, and feature fusion of information from effective receptive fields across a plurality of scales is performed, so as to adapt to sonar image targets of different sizes, thereby improving the accuracy and recognition speed in the recognition of an underwater acoustic target.

The invention provides an underwater acoustic target recognition method based on autonomous task perception, and belongs to the field of underwater acoustic signal processing and artificial intelligence. S3, performing feature extraction on the time-frequency spectrogram by the task type extraction network to obtain a task embedding vector, calculating a similarity score, when the maximum similarity score is greater than a set threshold value, outputting a task representation vector, and entering S3, otherwise, inputting features output by the last Transform layer into a classifier; s3, selecting a router according to the task representation vector, selecting a trained expert network by the router, calculating a door control weight, processing universal acoustic features in parallel by the expert network, fusing output of the expert network, fusing deep features and fused features to obtain enhanced features, and enabling the enhanced features output by the last Transform layer to enter a classifier; the invention further provides a system. The problems that the task category autonomous recognition capability is insufficient and the correlation between tasks is ignored are solved.

The invention provides a system for improving positioning precision under a complex underwater acoustic channel and an optimization method, and relates to the field of underwater positioning. The system for improving the positioning precision under the complex underwater acoustic channel comprises a time delay estimation module, a sound velocity profile data module, a sound ray correction module, a slope distance value precision module and a precision improvement module, and the time delay estimation module is mainly used for obtaining more accurate time delay data; the sound velocity profile data module is mainly used for acquiring sound velocity profile data of a positioning area. According to the method, a real sound ray path is estimated by using a sound ray correction method, measurement errors of bubbles in water, sound velocity change and position and propagation time are considered, the positioning precision is further improved, and the comprehensive optimization method enables the system to accurately reflect the real position of a target in a complex underwater environment, so that the positioning accuracy is improved. The overall performance of underwater target positioning is remarkably improved, and the actual requirement of high-precision positioning is met.

The invention relates to the technical field of submarine cable fault positioning, in particular to a submarine cable fault positioning system based on underwater beacons. The method comprises the steps that an underwater acoustic beacon array unit monitors and collects submarine cable fault sound wave signals in real time based on underwater acoustic beacons; the fault signal processing analysis unit extracts submarine cable fault sound wave signal parameters based on a non-point source space sound source waveform analysis model, and generates multi-parameter fault sound source feature vectors; the sound source positioning analysis algorithm unit performs three-dimensional inversion positioning based on the multi-parameter fault sound source feature vector and the arrival time difference of the submarine cable fault sound wave signal to the underwater acoustic beacon, and obtains the spatial position information of the submarine cable fault point; and the data communication alarm management unit sends the spatial position information of the submarine cable fault point to a shore-based operation and maintenance system. The submarine cable fault positioning method is used for realizing a submarine cable fault positioning technology for quickly and accurately positioning and identifying spatial extension characteristics in a complex submarine environment.

The invention relates to the technical field of underwater communication and positioning, in particular to a multi-mode underwater wireless communication system based on dynamic link calibration, which integrates underwater acoustic positioning guide, attitude adaptive tracking control, optical link enhancement and an error code correction mechanism. Comprising a central control core, an acoustic communication unit, an optical communication transmitting unit, an optical signal receiving unit, an optical control unit, a multi-axis attitude adjusting unit, a data fusion and verification processing unit and a high-speed modulation-demodulation and error code correction unit. And by using a double-shaft servo motor and automatic gain control, real-time target tracking and accurate alignment of optical signals are realized, FPGA and OFDM modulation are combined to optimize data throughput, and a data cross validation mechanism is introduced to correct error codes, so that the data integrity is improved.

The invention provides an underwater positioning system combining sound ray propagation modeling and multipath interference suppression, which relates to the technical field of marine equipment and comprises a self-adaptive underwater sound sensing and environment cognition module, an environment self-adaptive sound ray propagation modeling module, a multipath suppression and direct wave extraction module and a multi-dimensional information fusion and self-adaptive positioning calculation module. The self-adaptive underwater sound sensing and environment cognition module is used for realizing multi-mode sensing and real-time environment feature recognition of underwater sound signals, and the environment self-adaptive sound ray propagation modeling module is used for constructing a dynamically updated sound wave propagation model and providing a propagation path and time constraint for positioning calculation; the multi-path suppression and direct wave extraction module is used for carrying out multi-path signal separation and extracting direct wave features with confidence marks, and the multi-dimensional information fusion and self-adaptive positioning calculation module is used for completing high-precision positioning calculation; according to the system, deep fusion of an environment model and signal processing can be realized, and the positioning precision and robustness of the underwater vehicle in a complex underwater sound environment are remarkably improved.

The invention provides an anti-interference sound signal data extraction method based on energy data perception, and belongs to the technical field of underwater sound signal processing, and the method comprises the steps: carrying out the A / D sampling and digital orthogonal demodulation of a received sound signal, and obtaining a baseband signal; performing low-pass filtering and downsampling on the baseband signal to obtain a preprocessed signal; performing matched filtering on the pre-processed signal by using a reference signal; the key improvement lies in that a local energy estimation function of a preprocessed signal is calculated, and normalization processing is carried out on a matched filtering result and the energy estimation function to obtain a normalized detection signal. The method effectively suppresses the shielding effect of a strong interference signal on a weak target signal under a non-orthogonal reference signal and a strong near-end and weak far-end scene, remarkably reduces the misrecognition probability, and improves the accuracy and reliability of the extraction of a long-distance and low-signal-to-noise-ratio target beacon signal in a complex underwater acoustic environment. The method is suitable for underwater navigation, positioning and communication systems.

The invention belongs to the technical field of underwater acoustic engineering and digital signal processing, and particularly relates to a fractional delay FIR (Finite Impulse Response) phase calibration method and system of a multichannel sonar system. Comprising the steps of signal acquisition and reference channel selection; high-precision relative delay estimation; calculating a cross-correlation function of other channel signals and the reference channel signal, performing coarse estimation by searching a peak point of the amplitude of the cross-correlation function, and performing fine estimation on the peak position by using a parabola interpolation method to obtain the delay time of each channel relative to the reference channel; designing an FIR fractional delay filter; digital filtering and phase calibration; verifying a calibration effect; and calculating the phase of each channel signal at the target frequency point after calibration, and counting the standard deviation of each channel signal so as to evaluate the improvement degree of phase consistency. The method aims at overcoming the defect that traditional integral multiple sampling delay correction precision is insufficient, high-precision phase compensation of a sub-sampling point level is achieved, and therefore the performance of algorithms such as beam forming of a multi-channel sonar system is remarkably improved.

The invention belongs to the field of underwater acoustic networks, and relates to underwater Internet of Things, underwater environment monitoring, resource development and marine ecological protection. In order to provide an overall architecture of a simulation platform and an implementation technology of a core module of the overall architecture, and further enhance the simulation capability of an underlying protocol and a physical channel on the basis of being compatible with a standard network protocol stack and supporting seamless deployment of an existing application program, the invention provides an underwater Internet of Things semi-physical simulation system based on a container. Comprising a terminal host, a gateway node with underwater sound and wired network communication capabilities, and a plurality of real nodes which can be deployed underwater and have underwater sound communication capabilities, and an MAC simulation module and a channel simulation module are deployed on the terminal host and are used for constructing a simulation environment; and the semi-physical simulation interfaces are simultaneously deployed on the terminal host and the gateway node, so that traffic mapping in a simulation environment of the gateway node and the terminal host is realized. The method is mainly applied to design and manufacturing occasions of an underwater Internet of Things simulation system.

The invention discloses a high-frequency shallow water bottom reverberation signal modeling method, and belongs to the technical field of underwater acoustic engineering and signal processing. The method comprises the following steps: setting a modeling hypothesis; a cylindrical array geometric structure is constructed, scattering units are divided, and channel parameters and scattering functions are obtained in combination with a Bellhop tool and a GABIM model; generating a reverberation signal time domain expression, deducing an array receiving signal spatial domain expression and calculating a spatial spectrum; the model can also adjust underwater environment parameters to realize simulation under different conditions, and performs time domain and space domain theoretical analysis on reverberation signals based on a cylindrical array. Multi-dimensional underwater environment parameters are fused, and the modeling precision is improved; a receiving and transmitting combined cylindrical array is adapted, and spatial gain is embodied; experiments prove that the average error is within 3dB, the practicability is outstanding, support can be provided for design and optimization of the sonar system, and the method is suitable for underwater reverberation signal simulation and characteristic analysis of the sonar system in the high-frequency shallow water environment.

The invention discloses an open architecture system for an underwater acoustic signal processor, and belongs to the technical field of underwater acoustic signal processors. The system comprises a hardware resource pool, a standardized algorithm container group, a visual processing link construction module, a containerized deployment and scheduling platform and a data processing and communication plane. According to the system, special hardware resources are pooled, an underwater sound processing algorithm is packaged into a standardized container, a user is allowed to arrange a processing flow in a graphical mode, an intelligent scheduling platform dynamically deploys the algorithm container to matched hardware for execution according to real-time resource conditions, and meanwhile, an efficient and reliable data communication channel is provided. According to the method, the problems that a traditional system is closed, poor in expansibility and low in resource utilization rate are solved, elastic sharing of hardware resources, agile deployment of an algorithm and flexible construction of a flow are achieved, and openness, flexibility and overall efficiency of an underwater acoustic signal processing system are remarkably improved.

The invention relates to the field of underwater acoustic communication and detection, in particular to a waveform optimization method and system for an underwater acoustic detection and communication integrated system. According to the method, a constant modulus phase is taken as a constraint, a reserved subcarrier phase is taken as an optimization variable, and a multi-objective function for joint optimization of a peak-to-average power ratio and a non-periodic autocorrelation integral sidelobe ratio is constructed; a population is initialized, an objective function is evaluated, and a parent population is obtained through non-dominated sorting and crowding distance calculation; generating filial generations through selection, crossover and variation, combining the filial generations with the parent generations, and updating sorting and crowding distance to maintain population diversity; introducing a local gradient descent refinement mechanism, carrying out gradient iteration adjustment on an optimized individual under a constant modulus phase condition, and adaptively adjusting a crossover probability, a mutation probability and a phase variation scale according to a diversity evaluation result; and outputting a Pareto optimal solution set after the maximum number of iterations is reached, and obtaining an optimized sounding and communication integrated orthogonal frequency division multiplexing signal, so that the underwater communication and detection comprehensive performance can be effectively improved.

The invention relates to the technical field of underwater acoustic engineering and ocean exploration, in particular to a multi-channel underwater acoustic signal transmitting and measuring system and a signal processing method, which are used for solving the problems that the existing multi-channel underwater acoustic signal processing generally depends on fixed threshold detection or simple time sequence alignment, and the signal processing efficiency is low. The problem that residual vibration, local noise abrupt change or multipath reverberation is easily misjudged as an effective first arrival signal in a complex underwater environment due to the fact that the influence of the physical response characteristic of a transducer on emission time calibration is not considered and effective verification on whether a candidate arrival structure accords with a sound wave propagation physical rule is lacked is solved. According to the invention, a multi-channel energy time sequence and hydrophone space geometrical relationship is fused through an underwater sound propagation initial physical judgment module, a judgment mechanism is constructed based on distance-time consistency of sound propagation, and self-consistent verification is realized by combining a cross-channel arrival sequence and sound velocity constraint. And the accuracy, the robustness and the physical interpretability of the judgment of the effective launching time of the underwater sound are obviously improved.

The invention relates to the field of bionic hidden underwater acoustic communication, in particular to an underwater acoustic communication hidden performance evaluation method, device and equipment based on a neural network, and the method comprises the steps: carrying out the feature extraction of a to-be-evaluated underwater acoustic signal, and obtaining a feature sequence of the to-be-evaluated underwater acoustic signal; converting the feature sequence into a two-dimensional matrix with a preset size; the two-dimensional matrix is predicted according to a pre-trained underwater acoustic signal classification neural network model, a probability matrix is obtained, the probability matrix comprises a first probability and a second probability, the first probability represents the probability that the to-be-evaluated underwater acoustic signal belongs to the bionic modulation signal, and the second probability represents the probability that the to-be-evaluated underwater acoustic signal belongs to the bionic modulation signal; the second probability represents the probability that the underwater acoustic signal to be evaluated belongs to the real marine organism signal, and the underwater acoustic signal classification neural network model comprises an input layer, a first convolutional layer, a first pooling layer, a second convolutional layer, a second pooling layer, a global pooling layer and a full-connection output layer which are connected in sequence. The dependence on artificial feature design in a traditional recognition method is reduced, and the recognition stability in a complex underwater environment is improved.

The invention discloses a sparse regularization direction of arrival estimation method based on a risk minimization principle, and belongs to the technical field of array signal processing and underwater acoustic signal processing. The method comprises the steps of receiving array signals and establishing an observation model; constructing a sparse representation and over-complete dictionary; establishing and initializing a regularization optimization model; carrying out adaptive weight updating and risk-driven parameter selection; after regularization parameters are determined, a fast iterative shrinkage threshold algorithm FISTA is adopted to carry out optimization solution, and dictionary refinement is carried out on the detected direction after each iteration convergence so as to reduce off-grid errors; and after a small amount of outer layer iteration is repeated, outputting a final DOA estimation result and corresponding power. According to the method, self-adaptive selection of regularization parameters and noise levels can be realized, and the problem of precision degradation under complex conditions of low signal-to-noise ratio, limited snapshot number, signal source correlation, power imbalance and the like is effectively solved without manual parameter adjustment, so that the robustness and practicability of estimation are remarkably improved.

The invention discloses an underwater acoustic processing CPU-GPU dynamic load balancing method based on a task flow model, and belongs to the technical field of underwater acoustic processing. The method comprises the following steps: deconstructing an underwater acoustic processing application into a task flow model represented by a directed acyclic graph; establishing a feature portrait including calculation complexity, parallelism and data throughput for each task node, and constructing a cost prediction model; the CPU / GPU utilization rate and the data transmission performance are monitored in real time; a processor is distributed to each task node by using a dynamic programming algorithm in combination with a cost prediction model and a real-time system state with the goal of minimizing the total task flow completion time; and dynamically scheduling tasks through a central scheduler according to a decision result, and periodically updating a strategy. According to the method, the defects that static task division lacks adaptability and neglects task dependence and communication overhead are overcome, dynamic and efficient utilization of CPU and GPU resources is achieved, and the efficiency and real-time performance of underwater sound processing are remarkably improved.

The invention provides a motion compensation method and device for passive sonar detection. The compensation method comprises the following steps: acquiring underwater acoustic signals acquired by a passive sonar in real time within a preset period; performing segmentation processing and Fourier transform on the underwater acoustic signal to obtain an underwater acoustic frequency domain signal segment; constructing a parameterized search matrix of each water audio frequency domain signal segment, and determining a motion compensation parameter of each water audio frequency domain signal segment through similar energy spectrum search; based on the motion compensation parameter, performing phase compensation on the water audio frequency domain signal segment to obtain a compensation frequency domain signal segment; and performing inverse discrete Fourier transform on the compensation frequency domain signal segment to obtain a compensation time domain signal segment so as to determine a long-time coherent integration result corresponding to the underwater acoustic signal. Through the method, the gain of passive sonar detection processing is improved under the condition of low signal-to-noise ratio, and the accuracy and stability of passive sonar detection are improved.

According to the passive underwater cooperative positioning system and method provided by the invention, an intelligent signal processing and analysis module in the system receives a target underwater sound backscattering signal and a target environment parameter output by an environment adaptive feedback module, and then a path identification result and a positioning result are obtained by combining an identification model; obtaining a sound velocity correction value and a propagation time correction value based on the target environment parameters and a sound velocity correction model so as to obtain the moving speed of the target object; the cooperative positioning calculation module predicts the positioning information of the next moment based on the historical positioning information and the positioning information of the current moment; the environment self-adaptive feedback module receives the underwater sound backscattering signals generated by the multi-mode signal acquisition module and the acquired environment parameters, and transmits the underwater sound backscattering signals and the acquired environment parameters to the intelligent signal processing and analysis module as target underwater sound backscattering signals and target environment parameters; and the dynamic adjustment module is also used for dynamically adjusting the state parameters of the underwater acoustic backscattering signals and the environmental parameters so as to obtain new target underwater acoustic backscattering signals and target environmental parameters.

The invention provides a compensation balance system and method of an electrodynamic transducer, and aims to solve the following problems in the prior art: a traditional electrodynamic sound source transducer needs to realize large-volume displacement in a low-frequency application scene, but the flexibility of an elastic suspension support of the traditional electrodynamic sound source transducer is insufficient to bear hydrostatic pressure; meanwhile, traditional passive and active compensation modes have challenges in the aspects of delay and stability. In order to solve the problems, the compensation balance system and method of the electrodynamic transducer mainly comprise an underwater acoustic transducer, a low-pressure middle cabin and a high-pressure gas cylinder, and a system self-checking function, a transducer piston position balance control function and a transducer fuzzy self-adaptive control function are integrated. The defects in the prior art are effectively overcome, and balance between the inner cavity of the transducer and the external hydrostatic pressure can be rapidly achieved. In addition, the control process is further simplified by determining the target control quantity, and the overall performance of the system is improved.

The invention provides a spherical complex vibration type vector hydrophone based on an MEMS accelerometer, and relates to the technical field of underwater acoustic signal detection, and the spherical complex vibration type vector hydrophone comprises an MEMS accelerometer, a built-in core, a piezoelectric ceramic spherical shell, a sound transmission sealing shell, and a suspension ring. The MEMS accelerometer is orthogonally arranged in the built-in core; the built-in core is nested in the lower half ball of the piezoelectric ceramic spherical shell; the upper hemisphere of the perforated piezoelectric ceramic spherical shell is adhered to the upper edge of the built-in core; the sound transmission sealing shell coats the piezoelectric ceramic spherical shell through an encapsulation process; the suspension ring is bonded with the sound transmission sealing shell, and the hydrophone is suspended on the fixing support for use. The composite hydrophone can detect sound pressure signals and vibration velocity signals at the same position underwater, solves the problem of omnidirectional detection of the composite hydrophone on the sound pressure signals, and has the advantages of small size, simple structure, high reliability, wide application range and the like.

The invention discloses an underwater acoustic signal classification method based on comparative learning and feature fusion, and the method comprises the steps: collecting an original underwater acoustic signal, and carrying out the enhancement preprocessing of the original underwater acoustic signal, and obtaining a preprocessed underwater acoustic signal; outputting the preprocessed underwater acoustic signals to a classification neural network model to obtain an underwater acoustic signal classification result; wherein the classification neural network model is obtained according to the following steps: constructing a multi-modal heterogeneous feature fusion network; performing self-supervised comparison pre-training on the constructed multi-modal heterogeneous feature fusion network to obtain a pre-trained multi-modal heterogeneous feature fusion network; a classification module is built, and the classification module takes fusion features output by the multi-mode heterogeneous feature fusion network as input and takes probability distribution of each category as output; and performing progressive supervision fine tuning on the pre-trained multi-modal heterogeneous feature fusion network and the classification module to obtain a classification neural network model.

The invention belongs to the field of ocean robots, and particularly relates to an underwater acousto-optic fusion sensing method and system based on multi-scale space-time alignment. According to the invention, environment parameter data, a target distance and a low-resolution image are acquired through the data acquisition layer; establishing an acoustic effective distance model and an optical effective distance model, and generating acoustic features, optical features and a distance-confidence mapping function; adjusting the focal length and the wavelength and generating a 4K image; carrying out acousto-optic feature fusion through the acoustic features, the optical features and a confidence coefficient function, and outputting fusion features; performing observation updating by using space-time asynchronous compensation and motion prediction; according to the method, starting point and detection are utilized, system parameters are updated in real time through a multi-target algorithm, a sensing-optimization-feedback-iteration closed loop is formed, and the full-distance environment adaptability is improved. According to the invention, the problem of data fusion fault caused by inconsistent sensing distances of acoustic and optical sensors is solved, and high-precision target identification and positioning with full-distance coverage are realized.

The invention relates to the technical field of underwater acoustic signal processing in a sonar system, in particular to a large-aperture array robust adaptive waveform recovery method based on focusing covariance sparse reconstruction, and the method comprises the steps: carrying out the time-frequency transformation of all array element receiving time domain data, and obtaining array element domain-frequency domain data; constructing sampling covariance matrixes corresponding to different frequency points according to the array element domain-frequency domain data; constructing a multi-frequency-point focusing covariance matrix according to the sampling covariance matrix and the array manifold vector corresponding to each frequency point; constructing a sparse dictionary matrix adaptive to the focusing covariance matrix according to the linear relation between the focusing covariances of the frequency points, and obtaining a sparse expression of the focusing covariance matrix; according to the sparse representation form of the focusing covariance matrix, utilizing a sparse criterion to carry out iterative reconstruction on the focusing covariance matrix; and robust adaptive waveform recovery is carried out by using the focusing covariance matrix after sparse iteration reconstruction. According to the method, the short-time adaptive waveform recovery performance of the large-aperture array is remarkably improved.

The invention relates to the field of underwater acoustic detection, and discloses a high-resolution target orientation estimation method and device based on adjacent grid re-optimization, and the method comprises the steps: carrying out the expansion of an array manifold into a virtual array manifold, taking the virtual array manifold as a covariance matrix of an over-complete dictionary construction receiving signal, and carrying out the iterative updating of a noise signal component and a signal component; re-optimizing the adjacent grids to update the dictionary, and performing orientation estimation again in the re-divided intervals; and obtaining a direction-of-arrival estimation result through spectrum peak search. By applying the method, the orientation estimation performance of the underwater vehicle can be improved, and the DOA estimation performance with higher robustness and higher estimation precision can be obtained on a small array.

The invention discloses an underwater acoustic adaptive transmission method based on channel prediction, and belongs to the technical field of communication. The method comprises the following steps of: 1, designing a transmitting link of an underwater acoustic self-adaptive transmission system based on channel prediction; and 2, designing a receiving link of the underwater acoustic adaptive transmission system based on channel prediction. According to the method, chirp parameters are dynamically selected on a sending link based on a predicted channel state, then adaptive transmission is carried out on an imitated radio frequency division multiplexing signal, channel state information is estimated through embedded pilot frequency at a receiving end, channel characteristics are fully learned through a channel prediction model of Transform, and the channel state information is subjected to channel prediction. And the obtained accurate future channel state information is used for balancing and self-adaptive parameter adjustment, and the flexibility and the transmission reliability of underwater acoustic communication are improved by the method provided by the invention. The method is very suitable for a half-duplex-based underwater acoustic adaptive transmission system, and the excellent performance of the method is fully embodied.

The invention discloses an underwater acoustic target classification and identification method based on multi-domain feature deep fusion and multi-platform sonar data learning. The method comprises the following steps: firstly, preprocessing target tracking beam data collected by a multi-platform sonar, and constructing a time domain waveform sample set and a time-frequency spectrogram sample set; secondly, constructing an underwater acoustic target classification and recognition network model which comprises a primary feature extraction parallel double-branch network module and a feature deep fusion and classification recognition module, the primary feature extraction parallel double-branch network module extracts time domain and time frequency features respectively, and the feature deep fusion and classification recognition module realizes feature deep fusion and classification through a bidirectional cross attention mechanism; training the model by adopting a multi-stage training strategy, wherein the training comprises pre-training, special training, end-to-end training and fine tuning and incremental training; finally, unknown target data is preprocessed and then input into the trained model for forward reasoning, and a classification recognition result is output according to the majority voting principle. According to the method, target multi-domain information can be fully mined, multi-source data are effectively utilized, and the model generalization ability and the recognition precision are improved.

The invention discloses an underwater acoustic signal communication and positioning integrated method. The existing method does not jointly consider the problem of channel resource occupation caused by integration of communication and positioning. According to the method, mutually orthogonal Chirp subcarriers are used as communication signals, meanwhile, long Chirp signals are used as pilot frequency, and the pilot frequency and the communication signals are overlapped together to be sent at a sender, so that extra channel overhead caused by additional pilot frequency is saved, and the signal sending time interval is shortened. A receiver uses a plurality of pilot signals to perform joint Doppler estimation and compensation and time of arrival estimation, and the result of the time of arrival estimation is used for a positioning system and a communication system on the one hand. According to the demodulation mode, correlation calculation is carried out by using different Chirp subcarriers, and symbol demodulation is carried out according to correlation values. According to the communication and positioning integrated waveform design method, the signal sending time interval can be shortened, the system complexity can be reduced, and good communication performance is achieved.