67 results about "Side-scan sonar" patented technology

The invention discloses a complex underwater side-scan sonar exploration detection method and device based on a multi-dimensional attention collaborative lightweight anti-noise detection framework, and the device comprises an underwater side-scan sonar imaging device which is used for obtaining a sonar image of a detected target; the computer is connected with the underwater side-scan sonar imaging equipment and comprises a backbone feature extraction network module which is used for processing an input sonar image through a multi-scale edge refining module and outputting a three-scale feature map; the check feature fusion network module is used for realizing cross-channel and cross-space information fusion through the focusing space adaptive local attention module, performing adaptive modulation and deep information aggregation on multi-scale features through a channel frequency aggregation and attention mechanism, and outputting three enhanced feature maps; and the YOLOhead detection head module is used for generating a target detection frame according to the enhanced feature map, and outputting a detection result after non-maximum suppression processing.

The invention discloses a simulation platform for autonomous tracking of a subsea pipeline by a UUV. The simulation platform comprises a mother ship command and control node system used for issuing a task instruction to a UUV motion control and situation display system; the UUV motion control and situation display system is used for sending a course adjustment instruction to the UUV underwater unmanned vehicle and carrying out real-time graphical dynamic display on the navigation information of the UUV underwater unmanned vehicle; the UUV side-scan sonar model system is used for receiving the motion attitude information of the UUV underwater unmanned vehicle and carrying out detection result data production calculation on a target area in combination with the motion attitude information; the UUV subsea pipeline detection and identification system is used for carrying out pipeline identification according to side scanning detection result data and sending pipeline information to the UUV pipeline tracking strategy system; the UUV pipeline tracking strategy system is used for calculating the track information of the UUV underwater unmanned vehicle according to the pipeline information and the navigation information of the UUV underwater unmanned vehicle, and sending the track information to the mother ship command control node system.

The invention relates to the technical field of a seabed substrate advanced detection device and method for a seabed mining vehicle, and provides a seabed substrate advanced detection device and method for a seabed mining vehicle, which can simultaneously obtain submarine topography and landform and detect multiple parameters of a seabed substrate. The deep sea detection system is matched with a mine car to ensure smooth proceeding of a rear mine car in deep sea bottom detection, and comprises a sea surface data processing system and a frame with the cross section in a structure shaped like a Chinese character'tian ', a master control device, a signal receiver and at least four detection modules arranged in a matrix are arranged on the frame, and the master control device is used for controlling the detection modules. The signal receiver is used for transmitting information of the detection module and the sea surface receiving device; the detection module comprises a side-scan sonar module used for rapidly obtaining the topography and landform in front, a transverse push toothed plate used for cutting into a soil body, a turbidity meter module used for measuring the concentration of suspended particles and dissolved matters in the seabed, and a pressing plate module used for obtaining the bearing capacity and the subsidence index of the seabed sediment.

A split type AUV system comprises an autonomous underwater robot system and a buoy system, the autonomous underwater robot system comprises an electric control sealed cabin, a multi-beam imaging sonar module, a magnetic attraction fixing device, a visual positioning module, an ultra-short baseline USBL transponder beacon, a single-beam sonar module, a depth module, an underwater laser range finder, a battery sealed cabin and a driving unit; the buoy system comprises an ultra-short base line USBL beacon, a floating platform, a cable reel motor, a cable reel, a satellite positioning module, a buoy system electric control cabin, a side scan sonar, an Aruco two-dimensional code plate, a driving unit, a permanent magnet block and a battery cabin; the invention aims to provide an underwater navigation positioning system of a split type AUV (Autonomous Underwater Vehicle), which assists in acquiring the accurate position of an underwater robot.

The invention discloses a detection system for water level data and geological data of a weakly cemented coal seam, and belongs to the technical field of mine safety monitoring. Comprising a hardware layer and an algorithm layer, the hardware layer constructs a water surface-water body-water bottom three-in-one dynamic monitoring system, and the algorithm layer fuses multi-source data through a physical information neural network to realize global water bottom DEM inversion and dynamic early warning. And the physical information neural network inverts the global underwater DEM in a data driving item and physical driving item joint optimization mode by performing space-time alignment on the sonar point cloud, the unmanned aerial vehicle water level data and the optical fiber strain gradient and then performing weighted fusion. Sonar, optical fiber and water level data are fused through a PINN model, the crack recognition capacity is improved, and the side-scan sonar can detect cracks with the width larger than or equal to 2 cm; second-level data acquisition is achieved through the optical fiber sensor, the water inrush early warning response time is shortened, the response speed is increased, and the sonar sounding error is still controlled within 5 cm. The system robustness is increased, and the double-ring optical fiber network reduces the single-point fault influence range.

The invention belongs to the technical field of image processing, and discloses a side-scan sonar image feature extraction method and system, and the method employs an LF-Net network to carry out the feature point extraction of two adjacent side-scan sonar images, and employs a KNN algorithm to carry out the matching of the feature points extracted by the LF-Net. According to the method, a transfer learning mode is introduced based on the deep learning network LF-Net to solve the sonar image matching problem, side-scan sonar image feature point detection is carried out by constructing the pre-training actual measurement data matching model, and the problem that the generalization ability is poor due to the fact that the number of side-scan sonar image data is small is solved; the KNN algorithm is combined to realize accurate matching of acoustic image feature points, the matching result is subjected to statistical analysis to reduce the influence of mismatching, and the matching robustness is improved. According to the method, two adjacent side-scan sonar images can be accurately matched without too many side-scan sonar image data, and a brand new solution thought is provided for underwater sonar image matching in a complex scene.

The invention discloses an unmanned ship positioning method and system based on fusion of a side-scan sonar and an inertial sensor, and a medium. The method comprises the following steps: extracting ORB feature points from a side-scan sonar image; executing a parallel target detection algorithm on the side-scan sonar image to obtain semantic information of a current frame; screening background points and target points in combination with the depth of the feature points and semantic information of target detection; performing pose calculation based on an IMU (Inertial Measurement Unit) pre-integration method; according to the IMU resolving result and the feature point information, solving the initial pose value of the unmanned ship, and judging the dynamic and static conditions of the target; tight coupling optimization is carried out on the pose of the unmanned ship based on fusion information of the side-scan sonar and the inertial sensor, and a more accurate pose is obtained. According to the invention, fusion calculation is carried out on the side-scan sonar image and the measurement information of the inertial sensor, and semantic information of target detection is introduced, so that the unmanned ship can still realize high-precision and high-robustness real-time positioning in a complex dynamic marine environment.

The invention discloses a side-scan sonar echo simulation method, system and device fusing the influence of translation errors, and the method comprises the steps: carrying out the simulation of the echo of a side-scan sonar according to the motion speed and time of the side-scan sonar and the three-dimensional space position error information of the side-scan sonar deviating from ideal linear motion; calculating three-dimensional space coordinates when the side-scan sonar receives and transmits signals; respectively calculating a two-way slant range process between the side-scan sonar and each target in the space; performing corresponding time delay processing on the broadband signal transmitted by the transmitting array element; calculating a Doppler phase brought by the movement of the side-scan sonar relative to the target in a time domain, and adding a corresponding Doppler phase for the delayed signal; coherent accumulation is carried out on the echo signals of all the targets in the time domain to obtain simulation echo signals; and demodulating the simulation echo signal in the time domain to obtain a baseband echo signal. According to the side-scan sonar echo simulation method, the echo signal of the side-scan sonar can be simulated with high precision when the system has translation errors.

The utility model discloses a double-body unmanned ship side scan sonar measurement auxiliary device which comprises a double-body unmanned ship body, a fixing support is installed on the inner wall of the double-body unmanned ship body, a sleeve is installed at the other end of the fixing support, a probe rod is arranged in the inner wall of the sleeve in a sleeved mode, a top handle is arranged at the upper end of the probe rod, and a bottom handle is arranged at the lower end of the top handle. The outer wall of the feeler lever is provided with an up-down adjusting hole, the top end of the top handle is provided with a side-scan sonar data line, the inner wall of the sleeve is provided with a bolt, the feeler lever is provided with a connecting part, the lower end of the connecting part is provided with a semi-cylindrical clamping groove, and the front end of the semi-cylindrical clamping groove is provided with a protruding part. When the auxiliary device for measuring the side scan sonar of the double-body unmanned ship is used, the auxiliary device is made of stainless steel tube materials, is simple in structure, high in universality, easy to install at the center stabilizing part of the double-body unmanned ship, free of shaking during measurement, capable of improving data acquisition quality, low in manufacturing cost, high in applicability and easy to popularize.

The application belongs to the technical field of image processing, and discloses a side-scan sonar image feature extraction method and system, which extracts feature points of two adjacent side-scan sonar images by using an LF-Net network, and matches the feature points extracted by the LF-Net by using a KNN algorithm. The application introduces a transfer learning mode based on a deep learning network LF-Net to solve the sonar image matching problem, detects feature points of side-scan sonar images by constructing a pre-training measured data matching model, and solves the problem of poor generalization ability caused by the small amount of side-scan sonar image data. The application realizes accurate matching of sonar image feature points by combining the KNN algorithm, reduces the influence of false matching by statistically analyzing the matching results, and improves the robustness of matching. The application can accurately match two adjacent side-scan sonar images without too much side-scan sonar image data, and provides a new solution for underwater sonar image matching in complex scenes.

The invention relates to the technical field of underwater acoustic detection, and discloses a detection method for detecting silver carps and bighead carps on a large water surface based on a side-scan sonar technology, and the method comprises the steps: generating and transmitting an orthogonal multi-frequency coding pulse signal to a water body; receiving an echo signal formed by target scattering of the orthogonal multi-frequency coded pulse signal; processing the echo signal, and extracting a dynamic feature vector reflecting the moving attitude of the target; processing the echo signal, and extracting an actually measured resonance scattering spectrum reflecting acoustic characteristics of the target structure; calling a preset dynamic resonance correlation model based on the dynamic feature vector, and generating a predicted resonance scattering spectrum; and comparing the actually measured resonance scattering spectrum with the predicted resonance scattering spectrum, and calculating to obtain a dynamic matching score. A set of multi-dimensional and high-threshold identification criteria is established by constructing a high-dimensional fusion feature space containing dynamic features and dynamic matching scores and comparing the high-dimensional fusion feature space with a preset standard silver carp and bighead carp target feature domain.

A method for accurately segmenting submarine cables from side-scan sonar images comprises the following steps: inputting an image I1, processing the image I1 using a cable feature automatic extraction filter based on a curvelet transform, extracting cable-related information, and obtaining a feature image I2; pixel-by-pixel multiplying the image I1 by the feature image I2 to obtain a feature image I3; using a Hough transform to find no less than three straight line segments in the feature image I3, recording the angle α of the longest line segment in the image, constructing linear structural units in the same direction as the cables in the image, performing noise elimination and binarization processing on the feature image I3 to obtain a binary image I4; performing cable morphology restoration on the binary image I4 to obtain a cable morphology restoration image I5, and retaining only the largest connected area in the image as the cable segmentation result for the submarine side-scan sonar image. The method solves the problems in side-scan sonar image segmentation that a large amount of data is required for training, high image clarity requirements are required, target color information needs to be obtained, and high image size requirements are required.

The application provides a side scan sonar file processing method, and relates to the technical field of sonar image processing. The method comprises the following steps: acquiring block information according to the global image size of a side scan sonar file, wherein the block information comprises the total number of columns and the total number of rows of tiles; updating the pixel information of each tile based on the geographical range corresponding to the pulse strip and the tile of the side scan sonar file, wherein the pixel information comprises an image data array, an effective area marker array and a pixel count array; and generating an image file corresponding to each tile, wherein the image file comprises the pixel information, and the image file is used to generate a video corresponding to the side scan sonar file. The embodiment of the application can avoid memory overflow caused by loading global data at one time, greatly reduce memory consumption, independently output an image file for each tile, realize multi-thread parallelism, improve overall processing efficiency, and be suitable for different specifications of sonar files and hardware devices, and has strong engineering landing performance.

The utility model relates to an adjustable counterweight device based on a side-scan sonar tow fish, which can accurately increase and decrease counterweight lead blocks when the adjustable counterweight device is used for adjusting a tow posture based on sonar, and comprises a tow fish head and a suspension screw I, the counter weight comprises a circular plate, a fixed plate, a lead block and a suspension screw II; the adjustable balance weight comprises a circular plate II, a fixing plate II, a lead block II and a suspension screw III, the circular plate II and the fixing plate II are fixedly installed through screws, the lead block II, the circular plate II and the fixing plate II are fixedly assembled through heat-shrinkable sleeves, and the whole adjustable balance weight is suspended on the balance weight through the suspension screw II. According to the adjustable counterweight device, the lead blocks with different sizes are manufactured according to actual requirements, a plurality of adjustable counterweights are overlaid, and the circular plates and the fixing plates between the adjustable counterweights are combined and mounted, so that the adjustment of the counterweights is realized, and finally, the adjustment of the pitching posture of the tow fish is completed.

The invention belongs to the technical field of marine geological exploration, and particularly relates to a seabed sediment classification method and system based on a side-scan sonar image, and the method comprises the steps: introducing an acoustic imaging physical mechanism based on a Lambertian reflection model, carrying out the inversion of acoustic parameters of seabed sediments, and revealing the cause of echo intensity from the physical level; meanwhile, a superpixel segmentation algorithm is combined, analysis units with consistent structures are formed in space, noise interference is effectively reduced, and the salt and pepper phenomenon in pixel-level classification is avoided; furthermore, multi-source fusion is performed on image features, reflection features and topographic features, and the precision, the spatial continuity and the physical interpretability of seabed sediment classification are remarkably improved by utilizing the complementary advantage of multi-dimensional information. The method is suitable for seabed sediment classification in a complex terrain environment. The invention also provides a non-transitory readable recording medium storing the program of the method and a system comprising the medium, and the program can be called through a processing circuit to execute the method.

The application discloses a kind of side-scan sonar image seabed cable zero-sample rapid detection method, belong to seabed cable detection technical field, comprising the following steps: step one, establish neural network model;Step two, data fusion enhancement: to existing public side-scan sonar image data data fusion enhancement, generate experimental data set;Step three, data set annotation: to data set is marked;Step four, model training: neural network is trained;Step five, model test: using measured data to the network model after training is tested;The application, by establishing neural network model, and to existing public side-scan sonar image data data fusion enhancement, generate experimental data set, to data set is marked and neural network is trained, using measured data to the network model after training is tested, this method combines data enhancement method, realizes the zero-sample training and rapid detection of neural network.

The application discloses a side scan sonar echo simulation method, system and device fusing the influence of translational error, and the method comprises the following steps: according to the motion speed, motion time and three-dimensional space position error information of the side scan sonar deviating from ideal straight line motion, the three-dimensional space coordinates of the side scan sonar when transmitting and receiving signals are solved; the two-way slant range histories between the side scan sonar and each target in space are calculated respectively; the wideband signal transmitted by the transmitting array element is subjected to corresponding time delay processing; the Doppler phase caused by the relative motion between the side scan sonar and the target is calculated in the time domain, and the corresponding Doppler phase is added to the time-delayed signal; the echo signals of all targets are subjected to coherent accumulation in the time domain to obtain a simulation echo signal; and the simulation echo signal is demodulated in the time domain to obtain a baseband echo signal. The side scan sonar echo simulation method can simulate the echo signal of the side scan sonar when the system has translational error with high precision.

The application provides a kind of autonomous underwater vehicle seabed pipeline tracking method and device based on side scan sonar, it is related to underwater pipeline tracking technical field, the method comprises: during the control underwater robot is in pipeline investigation area and carries out comb search, utilize side scan sonar to continuously obtain seabed acoustic image;Pipeline track is detected based on seabed acoustic image, and the initial trajectory of pipeline is determined based on pipeline track;The state estimation of the pipeline is carried out based on the initial trajectory using Kalman filter;Based on state estimation result, the spatial length, confidence and continuity of initial trajectory are determined using trajectory quality evaluation method, and trajectory score is generated;In response to trajectory score meets preset requirement, the initial trajectory is determined as the target tracking trajectory of underwater robot;The front view distance and heading of the underwater robot are dynamically adjusted based on the target tracking trajectory.

The application discloses a kind of underwater robot navigation method, device and equipment based on side scan image matching.It relates to underwater robot navigation technical field, wherein method includes: in response to receiving underwater robot travels to target depth, the side scan sonar image of the underwater robot is preprocessed, and preprocessed image is obtained;Based on the image features of the preprocessed image and reference image in reference image database, feature matching is carried out, and relative pose constraint is obtained;Based on the relative pose constraint, current inertia data, current speed data and current depth data, the running state of the underwater robot is optimized using target fusion optimization method, and the optimized relative pose is obtained;Based on the optimized relative pose, the motion trajectory of the underwater robot is solved, and the navigation trajectory of the underwater robot is obtained.The method of the application can improve the accurate navigation ability of underwater robot in the scene lacking external base station or absolute speed measurement.

The application discloses a kind of based on dual attention mechanism's underwater side-scan sonar image recognition method and system, comprising: obtaining the monitoring image of underwater side-scan sonar equipment collection;Monitoring image is input to the EDA-Net model of pre-set and obtains underwater target detection result, wherein, EDA-Net model includes improved backbone network, improved neck network and head network;The improved backbone network is based on YOLOv11 framework construction, wherein double path heteromeric attention module is set;Improved neck network is provided with bottleneck convolution-parameterless attention module;The head network is used for target detection according to the feature map output by improved neck network.This application can more accurately identify target detail texture characteristics under the condition of small sample, multi-scale data set, improve the recognition accuracy and stability of model to multi-scale target in complex underwater environment.

The invention relates to the technical field of seafloor detection, in particular to a seafloor unexploded ordnance identification method and system based on multi-source data, and the method comprises the steps: obtaining seafloor surface multi-source detection data, and carrying out the preliminary screening of magnetic anomalies; suspected mine point magnetic anomaly screening based on mine magnetic moment modeling; pre-estimated burial depth screening of suspected thunder points; screening estimated weights of suspected thunder points; and performing refined verification on the suspected lightning point. According to the method, preliminary screening is carried out according to obtained unexploded ammunition magnetic anomaly data, and non-unexploded ammunition magnetic anomaly elimination is realized by combining geological information such as shallow stratum profile data, side-scan sonar data and synthetic aperture sonar data, a mine modeling and magnetic anomaly matching algorithm, a pre-estimated burial depth and pre-estimated weight screening method and the like. Finally, fine verification is carried out through a magnetic encryption detection method, and unexploded ordnance identification and positioning are achieved.

The invention relates to a subsea pipeline side-scan sonar detection method and device and electronic equipment, and relates to the technical field of multifunctional underwater robot target detection, and the method comprises the steps: inputting a side-scan sonar image into a deep learning model for feature extraction, determining a pipeline prediction result and a pipeline prediction confidence coefficient according to a prediction feature tensor, and obtaining a pipeline prediction result; identifying a pipeline target in the side-scan sonar image, and carrying out informatization processing on the pipeline target to generate a pipeline information dictionary; and performing post-processing optimization on the pipeline information dictionary, performing coordinate conversion on the pixel-level pipeline target image coordinates in the post-processed and optimized pipeline information dictionary in combination with the real-time navigation data, and resolving to obtain the longitude and latitude coordinates of the pipeline target. False detection targets which do not conform to pipeline features are effectively eliminated, so that the false alarm rate is reduced, and weak targets or subtle features of buried pipelines can be captured from complex sonar images.

The invention provides a target detection method for lightweight side-scan sonar shipwreck images, and the method comprises the steps: obtaining a target data set of side-scan sonar shipwreck detection, and the target data set comprises a plurality of shipwreck images; constructing an improved network model of the YOLO; the improved network model of the YOLO comprises a trunk improved network, a feature fusion improved network and a lightweight shared detection head; the main improved network comprises a plurality of layers of first improved cross-stage partial aggregation modules; the feature fusion improved network comprises a plurality of layers of second improved cross-stage partial aggregation modules and a plurality of layers of up-sampling improved modules; the lightweight sharing detection head comprises a sharing convolution module; training the improved network model by using the target data set to obtain a target improved network model; and acquiring a real-time data set of side-scan sonar shipwreck detection, and performing target detection on the real-time data set by using the target network model. According to the technical scheme, the problem that the existing side-scan sonar technology cannot have high precision and rapid detection at the same time is solved.

The present application relates to the technical field of underwater sonar detection, and discloses a region segmentation method and system for underwater target sonar image detection, comprising an image acquisition module, an algorithm optimization module and a verification and evaluation module. The region segmentation method and system for underwater target sonar image detection are connected to a side scan sonar through the image acquisition module to collect sonar image data of all regions, then utilize image processing software to perform data enhancement on the sonar data set and construct an experimental data set, the algorithm optimization module sets the YOLOv9 algorithm model as a real-time target detection framework, then introduces a BoTNet network and a SimAm attention mechanism for optimization and improvement, and is used for extracting feature information in the experimental data set, has strong feature capturing capability, the verification and evaluation module calculates the average precision mean and score of each algorithm model according to the experimental data set, compares the detection precision of the improved YOLOv9 algorithm model with the YOLOv3 algorithm model, the YOLOv5 algorithm model, the YOLOv7 algorithm model and the YOLOv9 algorithm model, and has high wreck detection precision.

A kind of shipboard solar tracking and hull stability device and water unmanned ship, it is related to unmanned ship design field, to solve the problem that how to prolong the operation time of unmanned ship when side scan sonar is carried on unmanned ship, and improve the imaging stability of side scan sonar again.The present application includes for adjusting the pitch angle of photovoltaic panel pitch adjusting support mechanism and for adjusting the position of pitch adjusting support mechanism longitudinal sliding drive mechanism, pitch adjusting support mechanism supports and can adjust the pitch angle of photovoltaic panel, when the altitude angle of sunlight changes, the incidence angle of sunlight relative to photovoltaic panel can be adjusted;Longitudinal sliding drive mechanism is installed to water unmanned ship, longitudinal sliding drive mechanism supports and can drive pitch adjusting support mechanism and photovoltaic panel reciprocating movement along the bow stern direction of water unmanned ship, when water unmanned ship is disturbed by wind and wave and shakes and oscillates, the longitudinal displacement of pitch adjusting support mechanism and photovoltaic panel is used to change the bow inclination characteristics of water unmanned ship, to resist wind and wave disturbance.

The application discloses a kind of underwater robot navigation method, device and equipment based on side scan image matching.It relates to underwater robot navigation technical field, wherein method includes: in response to receiving underwater robot travels to target depth, the side scan sonar image of the underwater robot is preprocessed, and preprocessed image is obtained;Based on the image features of the preprocessed image and reference image in reference image database, feature matching is carried out, and relative pose constraint is obtained;Based on the relative pose constraint, current inertia data, current speed data and current depth data, the running state of the underwater robot is optimized using target fusion optimization method, and the optimized relative pose is obtained;Based on the optimized relative pose, the motion trajectory of the underwater robot is solved, and the navigation trajectory of the underwater robot is obtained.The method of the application can improve the accurate navigation ability of underwater robot in the scene lacking external base station or absolute speed measurement.

The application discloses a kind of sonar image classification methods of combined SLIC superpixel and graph attention network.It includes the following steps: according to the imaging principle of two-dimensional forward-looking sonar and side scan sonar respectively and prior information when imaging: the sonar image after correction is based on the image pre-segmentation of improved DeepLabV3+ network, SLIC superpixel algorithm is used to construct Graph (graph) structure data: construct the sonar image classification model based on GAT (graph attention network), the sonar graph structure data built is sent into network to complete the training and test of model;Verify the importance of pixel feature and spatial position feature.The application discloses a kind of sonar image classification methods of combined SLIC superpixel and graph attention network, which fully utilizes the space position relationship of acoustic shadow area, target area and shadow area by SLIC superpixel method and graph attention network, so as to realize higher accuracy of sonar image classification identification of sonar image by combining pixel feature and spatial geometric feature.

The present application belongs to the technical field of marine geological exploration, and particularly relates to a seabed sediment classification method and system based on side-scan sonar images. By introducing an acoustic imaging physical mechanism based on a Lambertian reflection model, the inversion of acoustic parameters of seabed sediments can reveal the causes of echo intensity from a physical level. Meanwhile, combined with a superpixel segmentation algorithm, a structure-consistent analysis unit is formed in space, effectively reducing noise interference and avoiding the salt-and-pepper phenomenon in pixel-level classification. Further, multi-source fusion of image features, reflection features and terrain features is carried out, and the complementary advantages of multi-dimensional information are utilized, so that the precision, spatial continuity and physical interpretability of seabed sediment classification are significantly improved. The method of the present application is suitable for seabed sediment classification in complex terrain environments. The present application also provides a non-transitory readable recording medium storing a program of the method and a system comprising the medium, and the program can be called by a processing circuit to execute the above method.

The application discloses a kind of based on side scan sonar and inertial sensor fusion unmanned ship positioning method, system and medium, method includes: extracting ORB feature point from side scan sonar image;Parallel target detection algorithm is executed to side scan sonar image, and the semantic information of current frame is obtained;Combining feature point depth and the semantic information of target detection, background point and target point are screened;Pose solution is carried out based on IMU pre-integration method;According to IMU solution result and feature point information, the initial value of unmanned ship pose is solved, and the dynamic and static conditions of target are discriminated;Unmanned ship pose is tightly coupled optimization by based on side scan sonar and inertial sensor fusion information, and more accurate pose is obtained.The measurement information of side scan sonar image and inertial sensor is fused and calculated, and the semantic information of target detection is introduced, so that unmanned ship can still achieve high-precision, high-robustness real-time positioning in complex dynamic marine environment.

The application discloses a side scan sonar image row-by-row matching and splicing method based on numerical transformation processing, and comprises the following steps: acquiring a first sonar image and a second sonar image; traversing feature data of each row of the first sonar image and the second sonar image, performing one-dimensional wavelet transformation on each row of feature data sequences, and obtaining wavelet coefficients; constructing a feature vector based on the wavelet coefficients; calculating the similarity between the feature vector of each row of feature data in the first sonar image and the feature vectors of all rows of feature data in the second sonar image; identifying matching row pairs in the first sonar image and the second sonar image according to a set similarity threshold, determining a row offset and an overlapping region; aligning the first sonar image and the second sonar image according to the row offset and the overlapping region, and performing image fusion in the overlapping region to generate a panoramic sonar image. The application changes the matching dimension from two dimensions to one dimension, and solves the matching failure problem in a sparse feature environment.