Three-dimensional reconstruction method of underwater target based on single forward-looking sonar

Abstract

The application relates to the technical field of three-dimensional reconstruction, in particular to an underwater target three-dimensional reconstruction method based on a single forward-looking sonar. The method comprises the following steps: acquiring an acoustic frame sequence continuously collected by a single forward-looking sonar, and converting target observation information into range-azimuth observation data based on imaging parameters; associating the range-azimuth observation data with carrier pose data based on collection time information to obtain spatial pose data of each acoustic frame; determining the relative pose relationship between different acoustic frames based on the spatial pose data, and determining a target frame group according to the relative pose relationship; performing cross-frame corresponding point association based on the range-azimuth observation data of the target frame group, and performing geometric screening according to the relative pose relationship to obtain effective corresponding point data; taking the height angle parameters of the same target point in different acoustic frames as to-be-solved parameters for spatial consistency solving based on the effective corresponding point data and the relative pose relationship, obtaining three-dimensional coordinate data, and generating a three-dimensional reconstruction result of the underwater target.

Description

Technical Field

[0001] This application relates to the field of three-dimensional reconstruction technology, and in particular to a method for three-dimensional reconstruction of underwater targets based on a single forward-looking sonar. Background Technology

[0002] Underwater target 3D reconstruction is a crucial technology for aquaculture monitoring, cage structure inspection, underwater environmental sensing, and underwater mobile platform inspection. Existing underwater 3D reconstruction methods typically employ dual forward-looking sonar cross-observation or sonar-visual sensor fusion. The dual forward-looking sonar approach requires multiple sonar devices and demands stable installation orientation, time synchronization, and overlapping observation areas, resulting in high equipment costs, complex installation and debugging, and difficult long-term maintenance. While sonar-visual fusion can supplement insufficient sonar observations with visual information, visual image quality is prone to degradation in turbid, low-light, high-particulate, or heavily obstructed underwater environments. Furthermore, it requires calibration, synchronization, and registration between the sonar and camera, leading to high system deployment complexity. A single forward-looking sonar can typically directly obtain the target's distance, azimuth, and echo intensity information, but it struggles to directly obtain the target's height-angle information, resulting in height-direction uncertainty in the target observation information within a single acoustic image frame. Relying solely on single-frame acoustic images for 3D reconstruction can easily lead to incomplete 3D structures. Furthermore, simply overlaying consecutive acoustic frames is susceptible to variations in carrier pose, invalid observation baselines, and cross-frame mismatches, resulting in poor accuracy in 3D reconstruction of underwater targets using a single forward-looking sonar. Therefore, improving the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar has become a pressing technical problem. Summary of the Invention

[0003] The main objective of this application is to provide a method for three-dimensional reconstruction of underwater targets based on a single forward-looking sonar, aiming to solve the technical problem of how to improve the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar.

[0004] To achieve the above objectives, this application provides a method for three-dimensional reconstruction of underwater targets based on a single forward-looking sonar, the method comprising the following steps: Acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. Based on the acquisition time information corresponding to the acoustic frame sequence, the range and orientation observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame. The relative pose relationship between different acoustic frames is determined based on the spatial pose data, and the target frame group is determined from the acoustic frame sequence according to the relative pose relationship. Based on the range and orientation observation data corresponding to the target frame group, cross-frame corresponding points are associated, and the cross-frame corresponding points are geometrically filtered according to the relative pose relationship to obtain valid corresponding point data. Based on the effective corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency, so as to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data.

[0005] In one embodiment, the step of acquiring a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and converting the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence, includes: The raw sonar data stream output by the single forward-looking sonar during continuous acquisition is obtained, and the distance sampling information, azimuth sampling information, echo intensity information and acquisition time information in the raw sonar data stream are analyzed to obtain continuous sonar acquisition data. Based on the range sampling information, azimuth sampling information, and echo intensity information in the continuous sonar acquisition data, imaging mapping processing is performed to generate the acoustic frame sequence with range direction and azimuth direction as coordinate dimensions and echo intensity as pixel representation. Based on the sonar range information, azimuth sampling information and pixel position relationship corresponding to the acoustic frame sequence, coordinate mapping processing is performed on the target observation information in the acoustic frame sequence to obtain the range and azimuth observation data corresponding to the target observation information.

[0006] In one embodiment, the step of correlating the range and orientation observation data with the carrier pose data based on the acquisition time information corresponding to the acoustic frame sequence to obtain the spatial pose data corresponding to each acoustic frame includes: The carrier pose data corresponding to the acquisition of the acoustic frame sequence by the single forward-looking sonar is obtained, and the pose time information, position description information and attitude description information in the carrier pose data are parsed to obtain the carrier motion state data. Based on the acquisition time information corresponding to the acoustic frame sequence and the pose time information corresponding to the carrier motion state data, the distance and orientation observation data and the carrier motion state data are time-aligned to obtain frame pose association data corresponding to each acoustic frame. Based on the frame pose association data, coordinate representation processing is performed on the position description information and attitude description information corresponding to each acoustic frame to obtain the spatial pose data corresponding to each acoustic frame.

[0007] In one embodiment, the step of determining the relative pose relationship between different acoustic frames based on the spatial pose data, and determining the target frame group from the acoustic frame sequence according to the relative pose relationship, includes: Based on the spatial pose data, a reference acoustic frame and a candidate acoustic frame to be compared are determined from the acoustic frame sequence, and the first spatial pose data corresponding to the reference acoustic frame and the second spatial pose data corresponding to the candidate acoustic frame are extracted. Based on the first spatial pose data and the second spatial pose data, inter-frame pose transformation analysis is performed to determine the relative rotation relationship and relative translation relationship between the reference acoustic frame and the candidate acoustic frame, and the relative pose relationship is obtained based on the relative rotation relationship and the relative translation relationship. Based on the relative pose relationship, the observation baseline state between the reference acoustic frame and the candidate acoustic frame is determined, and the reference acoustic frame and candidate acoustic frame that meet the preset observation conditions are determined as the target frame group.

[0008] In one embodiment, the step of associating cross-frame corresponding points based on the range and azimuth observation data corresponding to the target frame group, and geometrically filtering the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data includes: Based on the target observation area corresponding to each acoustic frame in the target frame group, the observation points to be associated are extracted from the range and azimuth observation data corresponding to the target frame group, and cross-frame matching processing is performed on the observation points to be associated in different acoustic frames to obtain cross-frame corresponding point data. Based on the relative pose relationship, spatial mapping processing is performed on the corresponding observation points in the cross-frame corresponding point data located in different acoustic frames to obtain the geometric association representation data corresponding to the cross-frame corresponding point data. Based on the geometric correlation characterization data, the corresponding observation points in the cross-frame corresponding point data are filtered for horizontal and height deviations, and the cross-frame corresponding point data that meet the preset geometric consistency conditions are determined as the valid corresponding point data.

[0009] In one embodiment, the step of using the height-angle parameter of the same target point in different acoustic frames as the parameter to be solved for spatial consistency based on the effective corresponding point data and the relative pose relationship to obtain the three-dimensional coordinate data corresponding to the target point, and generating the three-dimensional reconstruction result of the underwater target based on the three-dimensional coordinate data, includes: Based on the effective corresponding point data, the distance and orientation observation data of the same target point in different acoustic frames are determined, and the height-direction angle parameter of the same target point in different acoustic frames is determined as the parameter to be determined; Based on the distance and orientation observation data, the parameters to be determined, and the relative pose relationship, a spatial consistency constraint for the same target point is constructed between different acoustic frames, and the parameters to be determined are constrained and solved to obtain the three-dimensional coordinate data corresponding to the target point. Based on the spatial pose data, the three-dimensional coordinate data is transformed to a unified coordinate system, and the transformed three-dimensional coordinate data is fused to obtain the three-dimensional reconstruction result of the underwater target.

[0010] Furthermore, to achieve the above objectives, this application also proposes an underwater target 3D reconstruction device based on a single forward-looking sonar, the underwater target 3D reconstruction device based on a single forward-looking sonar comprising: The information conversion module is used to acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. The association processing module is used to perform association processing on the range and orientation observation data and the carrier pose data based on the acquisition time information corresponding to the acoustic frame sequence, so as to obtain the spatial pose data corresponding to each acoustic frame. The target frame group module is used to determine the relative pose relationship between different acoustic frames based on the spatial pose data, and to determine the target frame group from the acoustic frame sequence according to the relative pose relationship. The geometric filtering module is used to associate cross-frame corresponding points based on the distance and orientation observation data corresponding to the target frame group, and to perform geometric filtering on the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data. The 3D reconstruction module is used to solve for spatial consistency by taking the height-angle parameter of the same target point in different acoustic frames as the parameter to be solved based on the effective corresponding point data and the relative pose relationship, so as to obtain the 3D coordinate data corresponding to the target point, and generate the 3D reconstruction result of the underwater target based on the 3D coordinate data.

[0011] Furthermore, to achieve the above objectives, this application also proposes an underwater target 3D reconstruction device based on a single forward-looking sonar. The device includes: a memory, a processor, and an underwater target 3D reconstruction program based on a single forward-looking sonar stored in the memory and executable on the processor. The underwater target 3D reconstruction program based on a single forward-looking sonar is configured to implement the steps of the underwater target 3D reconstruction method based on a single forward-looking sonar as described above.

[0012] In addition, to achieve the above objectives, this application also proposes a storage medium storing a three-dimensional underwater target reconstruction program based on a single forward-looking sonar. When the single forward-looking sonar-based three-dimensional underwater target reconstruction program is executed by a processor, it implements the steps of the three-dimensional underwater target reconstruction method based on a single forward-looking sonar as described above.

[0013] In addition, to achieve the above objectives, this application also proposes a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar as described above.

[0014] This application acquires a sequence of acoustic frames continuously collected by a single forward-looking sonar, and converts the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. Based on the acquisition time information corresponding to the acoustic frame sequence, the range and azimuth observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame. Based on the spatial pose data, the relative pose relationship between different acoustic frames is determined, and the target frame group is determined from the acoustic frame sequence according to the relative pose relationship. Based on the range and azimuth observation data corresponding to the target frame group, cross-frame corresponding points are correlated, and the cross-frame corresponding points are geometrically filtered according to the relative pose relationship to obtain effective corresponding point data. Based on the effective corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data. This application first converts target observation information in an acoustic frame sequence into range-azimuth observation data, providing a basis for spatial computation. Then, based on acquisition time information, it correlates the range-azimuth observation data with the carrier pose data to obtain spatial pose data corresponding to each acoustic frame, providing a basis for spatial correlation of observation information in different acoustic frames. Subsequently, it determines relative pose relationships based on the spatial pose data and uses this to determine target frame groups, ensuring that the acoustic frames involved in reconstruction have relative observation relationships that can be used for cross-frame constraints. Furthermore, it correlates corresponding points across frames based on the target frame groups and performs geometric filtering based on relative pose relationships, reducing the number of corresponding points that do not conform to inter-frame spatial relationships from participating in the solution. Finally, it uses the altitude-angle parameter of the same target point in different acoustic frames as a parameter to be solved for spatial consistency, obtaining three-dimensional coordinate data and generating three-dimensional reconstruction results. Thus, through the coordinated operation of range-azimuth observation conversion, pose correlation, frame group determination, corresponding point filtering, and altitude-angle parameter solving, the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar is improved. Attached Figure Description

[0015] Figure 1This is a flowchart illustrating the first embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application. Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application; Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application; Figure 4 This is a schematic diagram of the sonar coordinate system in one embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application; Figure 5 This is a schematic diagram of the three-dimensional reconstruction result of a lake nearshore scene in one embodiment of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in this application; Figure 6 This is a schematic diagram of the three-dimensional reconstruction result of a water tank test scene in one embodiment of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in this application; Figure 7 This is a diagram of an actual test scene in a water tank in one embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application. Figure 8 This is a schematic diagram of the module structure of the underwater target three-dimensional reconstruction device based on a single forward-looking sonar according to an embodiment of this application; Figure 9 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the underwater target 3D reconstruction method based on a single forward-looking sonar in the embodiments of this application.

[0016] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0018] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0019] It should be noted that underwater target 3D reconstruction is a crucial technology in aquaculture monitoring, cage structure inspection, underwater environmental sensing, and underwater mobile platform inspection. Existing underwater 3D reconstruction methods typically employ dual forward-looking sonar cross-observation or sonar-visual sensor fusion. The dual forward-looking sonar approach requires multiple sonar devices and demands stable installation orientation, time synchronization, and overlapping observation areas, resulting in high equipment costs, complex installation and debugging, and significant long-term maintenance challenges. While sonar-visual fusion can supplement insufficient sonar observations with visual information, visual image quality is prone to degradation in turbid, low-light, high-particulate, or heavily obstructed underwater environments. Furthermore, calibration, synchronization, and registration between the sonar and camera are necessary, leading to high system deployment complexity. A single forward-looking sonar can typically directly obtain the target's distance, azimuth, and echo intensity information, but it struggles to directly obtain the target's height-direction angle information, resulting in height-direction uncertainty in the target observation information within a single acoustic image frame. Relying solely on single-frame acoustic images for 3D reconstruction can easily lead to incomplete 3D structures. Furthermore, simply overlaying consecutive acoustic frames is susceptible to variations in carrier pose, invalid observation baselines, and cross-frame mismatches, resulting in poor accuracy in 3D reconstruction of underwater targets using a single forward-looking sonar. Therefore, improving the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar has become a pressing technical problem.

[0020] The main solution of this application is as follows: Acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence; based on the acquisition time information corresponding to the acoustic frame sequence, perform correlation processing on the range and azimuth observation data and the carrier pose data to obtain the spatial pose data corresponding to each acoustic frame; determine the relative pose relationship between different acoustic frames based on the spatial pose data, and determine the target frame group from the acoustic frame sequence according to the relative pose relationship; perform cross-frame corresponding point correlation based on the range and azimuth observation data corresponding to the target frame group, and perform geometric filtering on the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data; based on the valid corresponding point data and the relative pose relationship, use the height-angle parameter of the same target point in different acoustic frames as the parameter to be solved for spatial consistency to obtain the three-dimensional coordinate data corresponding to the target point, and generate the three-dimensional reconstruction result of the underwater target based on the three-dimensional coordinate data.

[0021] This application first converts target observation information in an acoustic frame sequence into range-azimuth observation data, providing a basis for spatial computation. Then, based on acquisition time information, it correlates the range-azimuth observation data with the carrier pose data to obtain spatial pose data corresponding to each acoustic frame, providing a basis for spatial correlation of observation information in different acoustic frames. Subsequently, it determines relative pose relationships based on the spatial pose data and uses this to determine target frame groups, ensuring that the acoustic frames involved in reconstruction have relative observation relationships that can be used for cross-frame constraints. Furthermore, it correlates corresponding points across frames based on the target frame groups and performs geometric filtering based on relative pose relationships, reducing the number of corresponding points that do not conform to inter-frame spatial relationships from participating in the solution. Finally, it uses the altitude-angle parameter of the same target point in different acoustic frames as a parameter to be solved for spatial consistency, obtaining three-dimensional coordinate data and generating three-dimensional reconstruction results. Thus, through the coordinated operation of range-azimuth observation conversion, pose correlation, frame group determination, corresponding point filtering, and altitude-angle parameter solving, the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar is improved.

[0022] It should be noted that the execution subject of the method in this embodiment can be a computing service device with data processing, network communication, and program execution functions, or it can be the aforementioned underwater target 3D reconstruction device based on a single forward-looking sonar with the same or similar functions. This embodiment and the following embodiments will be described using an underwater target 3D reconstruction device based on a single forward-looking sonar as an example.

[0023] Based on this, a first embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar is proposed in this application. Please refer to [link / reference]. Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application.

[0024] In this embodiment, the method includes the following steps: S1: Acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. S2: Based on the acquisition time information corresponding to the acoustic frame sequence, the range and orientation observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame; S3: Determine the relative pose relationship between different acoustic frames based on the spatial pose data, and determine the target frame group from the acoustic frame sequence according to the relative pose relationship; It should be noted that a single forward-looking sonar refers to a single acoustic imaging device used to transmit acoustic pulses into the water ahead of a carrier and receive reflected echoes; an acoustic frame sequence refers to multiple acoustic images or acoustic data frames formed in chronological order during continuous acquisition by a single forward-looking sonar; imaging parameters refer to parameters used to convert pixel positions in an acoustic frame into acoustic observations, including sonar range, range sampling information, azimuth sampling information, and pixel position correspondence; target observation information refers to pixel regions, echo intensity distribution, or target acoustic response information related to the underwater target to be reconstructed in the acoustic frame; range and azimuth observation data... The data refers to the distance and orientation of the target relative to the forward-looking sonar, which is obtained by converting the target observation information; the acquisition time information refers to the acquisition time or time marker corresponding to each acoustic frame; the carrier pose data refers to the position and attitude data of the carrier carrying the forward-looking sonar during the acquisition process; the spatial pose data refers to the spatial position and attitude representation data corresponding to each acoustic frame; the relative pose relationship refers to the position and attitude change relationship between the spatial pose data corresponding to different acoustic frames; and the target frame group refers to the combination of acoustic frames that meet the preset observation conditions and are used for subsequent cross-frame reconstruction, determined from the acoustic frame sequence.

[0025] Specifically, in implementation, the acoustic data output by a single forward-looking sonar during continuous acquisition is first received. An acoustic frame sequence is then generated based on the range sampling information, azimuth sampling information, and echo intensity information within the acoustic data. For each acoustic frame in the sequence, the target observation information is analyzed by combining the sonar range, azimuth sampling range, and pixel position correspondence. This converts the target information, originally existing as pixel regions or echo intensity, into range and azimuth observation data, transforming the image-level acoustic response into observation data usable for subsequent spatial correlation and 3D solution.

[0026] Then, based on the acquisition time information corresponding to each acoustic frame in the acoustic frame sequence, the range and orientation observation data corresponding to each acoustic frame are temporally correlated with the carrier pose data to determine the carrier position and attitude corresponding to the acquisition time of each acoustic frame. If the acquisition time of the acoustic frame and the acquisition time of the carrier pose are not completely consistent, adjacent carrier pose data can be matched or interpolated based on the acquisition time information to obtain the spatial pose data corresponding to each acoustic frame. Subsequently, based on the spatial pose data corresponding to different acoustic frames, the relative pose relationship between acoustic frames is determined, and based on this relative pose relationship, it is determined whether different acoustic frames possess the observation conditions for cross-frame spatial constraints, thus identifying the target frame group from the acoustic frame sequence.

[0027] By converting target observation information in the acoustic frame sequence into range and azimuth observation data, the imaged target information acquired by a single forward-looking sonar has an observational basis that can be used for spatial computation. By associating the range and azimuth observation data with the carrier pose data using acquisition time information, the target observation information in each acoustic frame obtains corresponding spatial pose constraints. Based on this, the relative pose relationships between different acoustic frames are determined according to the spatial pose data, and the target frame group is determined accordingly. This reduces the participation of acoustic frames with unclear spatial relationships or unsuitable observation conditions in subsequent reconstruction. Therefore, the above steps provide spatiotemporally consistent input data for subsequent cross-frame corresponding point association and 3D coordinate solution, helping to improve the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0028] S4: Based on the range and orientation observation data corresponding to the target frame group, perform cross-frame corresponding point association, and perform geometric filtering on the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data; S5: Based on the effective corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency, so as to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data.

[0029] It should be noted that cross-frame correspondence refers to the process of finding observation points corresponding to the same underwater target point or the same local structure of the target across different acoustic frames in a target frame group; cross-frame correspondence points refer to observation points located in different acoustic frames but considered to correspond to the same target point; geometric screening refers to judging whether cross-frame correspondence points conform to spatial positional relationships based on the relative pose relationships between different acoustic frames and removing unreliable correspondence points; valid correspondence point data refers to the cross-frame correspondence point data retained after geometric screening that can participate in subsequent spatial consistency solutions; the height-direction angle parameter refers to the parameter used to characterize the target point relative to the acoustic plane. The parameters are: angular parameters of the observation direction's deflection in the height direction; parameters to be determined, which are parameters that cannot be directly obtained from single-frame acoustic observations during the 3D coordinate solution process and need to be determined through cross-frame spatial constraints; spatial consistency solution, which refers to the process of using observation data of the same target point in different acoustic frames and the relative pose relationship between corresponding acoustic frames to keep the target point in the same spatial position in different frames and thus solve the 3D position of the target point; 3D coordinate data, which refers to the data used to characterize the position of the target point in 3D space; and 3D reconstruction result, which refers to the underwater target spatial structure expression result formed based on the 3D coordinate data of multiple target points.

[0030] Specifically, in implementation, for a determined target frame group, the range and orientation observation data corresponding to each acoustic frame in the target frame group are first extracted, and corresponding point association processing is performed between different acoustic frames in the target frame group. This corresponding point association can be performed around the observation points in the target area to be reconstructed, establishing a correspondence between target observation points located in different acoustic frames, thus obtaining cross-frame corresponding points. Subsequently, based on the relative pose relationship between different acoustic frames in the target frame group, the spatial relationship of the cross-frame corresponding points is judged. For example, the corresponding observation points in different acoustic frames are spatially mapped according to the relative pose relationship, and their consistency in spatial position is compared, thereby identifying corresponding points that obviously do not conform to the inter-frame geometric relationship. Cross-frame corresponding points that do not meet the geometric consistency condition are discarded as unreliable corresponding points; cross-frame corresponding points that meet the geometric consistency condition are retained as valid corresponding point data.

[0031] For valid correspondence point data, since a single forward-looking sonar can provide range and azimuth observations but cannot directly provide the height angle information of the target point, the height angle parameter of the same target point in different acoustic frames is used as a parameter to be determined. Then, by combining the range and azimuth observation relationship in the valid correspondence point data and the relative pose relationship corresponding to the target frame group, a constraint relationship is established that the same target point should correspond to the same spatial position in different acoustic frames, and the height angle parameter is determined by solving for spatial consistency. After obtaining the height angle parameter, the position of the target point in three-dimensional space can be determined by combining the range and azimuth observation data, obtaining the three-dimensional coordinate data corresponding to the target point, and generating the three-dimensional reconstruction result of the underwater target based on the three-dimensional coordinate data of multiple target points.

[0032] By associating corresponding points across frames of range and azimuth observation data for target frames, an observational correspondence can be established for the same target point in different acoustic frames. Furthermore, geometric filtering of these cross-frame corresponding points, combined with relative pose relationships, reduces the participation of mismatched points or spatially inconsistent corresponding points in subsequent solutions. Based on this, the altitude angle parameter is used as a parameter to achieve spatial consistency, allowing altitude information that is difficult to obtain directly from a single forward-looking sonar to be determined through cross-frame observation relationships and relative pose relationships. Therefore, these steps reduce the impact of cross-frame mismatches and missing altitude observations on 3D coordinate solutions, making the obtained 3D coordinate data more consistent with the actual spatial relationships of the target point, thereby improving the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0033] This embodiment acquires a sequence of acoustic frames continuously collected by a single forward-looking sonar, and converts the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. Based on the acquisition time information corresponding to the acoustic frame sequence, the range and azimuth observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame. Based on the spatial pose data, the relative pose relationship between different acoustic frames is determined, and the target frame group is determined from the acoustic frame sequence according to the relative pose relationship. Based on the range and azimuth observation data corresponding to the target frame group, cross-frame corresponding points are correlated, and the cross-frame corresponding points are geometrically filtered according to the relative pose relationship to obtain valid corresponding point data. Based on the valid corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data. This embodiment first converts target observation information in the acoustic frame sequence into range and azimuth observation data, providing a basis for spatial computation. Then, based on acquisition time information, the range and azimuth observation data is correlated with the carrier pose data to obtain spatial pose data corresponding to each acoustic frame, providing a basis for spatial correlation of observation information in different acoustic frames. Subsequently, relative pose relationships are determined based on the spatial pose data, and target frame groups are identified accordingly, ensuring that the acoustic frames participating in the reconstruction have relative observation relationships that can be used for cross-frame constraints. Further, cross-frame corresponding point correlation is performed based on the target frame groups, and geometric screening is conducted in conjunction with relative pose relationships to reduce the number of corresponding points that do not conform to inter-frame spatial relationships from participating in the solution. Finally, the altitude-angle parameter of the same target point in different acoustic frames is used as a parameter to solve for spatial consistency, obtaining three-dimensional coordinate data and generating three-dimensional reconstruction results. Thus, through the coordinated operation of range and azimuth observation conversion, pose correlation, frame group determination, corresponding point screening, and altitude-angle parameter solving, the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar is improved.

[0034] Based on the first embodiment described above, a second embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar is proposed in this application. Please refer to... Figure 2 , Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in this application.

[0035] like Figure 2 As shown, in this embodiment, step S1 includes: S11: Obtain the raw sonar data stream output by the single forward-looking sonar during continuous acquisition, and parse the distance sampling information, azimuth sampling information, echo intensity information and acquisition time information in the raw sonar data stream to obtain continuous sonar acquisition data. S12: Based on the range sampling information, azimuth sampling information and echo intensity information in the continuous sonar acquisition data, perform imaging mapping processing to generate the acoustic frame sequence with range direction and azimuth direction as coordinate dimensions and echo intensity as pixel representation; S13: Based on the sonar range information, azimuth sampling information and pixel position relationship corresponding to the acoustic frame sequence, coordinate mapping processing is performed on the target observation information in the acoustic frame sequence to obtain the range and azimuth observation data corresponding to the target observation information.

[0036] It should be noted that the raw sonar data stream refers to the raw acoustic acquisition data output by the forward-looking sonar during continuous operation, which may include sonar video stream, echo intensity data stream, or range-azimuth-intensity data; range sampling information refers to the sampling data obtained by dividing the echo signal according to the range direction, used to characterize the distance relationship between the target and the sonar; azimuth sampling information refers to the angle sampling data obtained by dividing the echo signal according to the horizontal field of view, used to characterize the azimuth distribution of the target relative to the sonar; echo intensity information refers to the reflection intensity information of the sound wave after encountering an underwater target or scene and returning to the sonar receiver, used to characterize the acoustic response level at the corresponding location; continuous sonar acquisition data is... This refers to continuous data formed after parsing the raw sonar data stream, containing information such as range sampling, azimuth sampling, echo intensity, and acquisition time; imaging mapping processing refers to the process of organizing continuous sonar acquisition data into acoustic frames according to the range and azimuth directions; sonar range information refers to the range of distances that forward-looking sonar can detect; azimuth sampling information refers to the azimuth angle division data corresponding to the sonar within the horizontal field of view; pixel position relationship refers to the correspondence between pixel positions and range sampling positions and azimuth sampling positions in the acoustic frame; coordinate mapping processing refers to the process of converting target observation information from pixel representation to range and azimuth representation based on sonar range, azimuth sampling, and pixel position relationship.

[0037] Specifically, in implementation, the system first receives the raw sonar data stream output by a single forward-looking sonar during continuous acquisition. This raw data stream is then parsed to identify the range sampling information, azimuth sampling information, echo intensity information, and acquisition time information contained within it. Through this parsing process, the raw acoustic data is transformed from the device's output format into continuous sonar acquisition data that is easy to process later. This ensures that the acoustic data at each acquisition moment contains basic information such as range direction, azimuth direction, echo intensity, and time stamp.

[0038] Furthermore, based on the range and azimuth sampling information from the continuous sonar acquisition data, the arrangement relationship of acoustic data in the range and azimuth directions is established, and the echo intensity information at the corresponding position is used as pixel representation to generate an acoustic frame sequence. Subsequently, for the target observation information in the acoustic frame sequence, combined with the sonar range information, azimuth sampling information, and pixel position relationship, the range and azimuth positions corresponding to the pixel positions of each target observation point in the acoustic frame are determined, and the target observation information is converted into corresponding range and azimuth observation data.

[0039] By analyzing the range sampling information, azimuth sampling information, echo intensity information, and acquisition time information in the raw sonar data stream, the raw acoustic data continuously acquired by the forward-looking sonar can be transformed into structured continuous sonar acquisition data. Through imaging mapping based on range direction, azimuth direction, and echo intensity, the continuous sonar acquisition data can be organized into an acoustic frame sequence that facilitates target observation and subsequent processing. Furthermore, by combining sonar range information, azimuth sampling information, and pixel positional relationships for coordinate mapping, target observation information can be transformed from image pixel-level representations into physically meaningful range and azimuth observation data. Therefore, the above steps provide an accurate observation input foundation for subsequent pose correlation, cross-frame matching, and 3D coordinate solution, contributing to improving the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0040] Based on the first embodiment described above, in this embodiment, step S2 includes: S21: Obtain the carrier pose data corresponding to the process of the single forward-looking sonar acquiring the acoustic frame sequence, and parse the pose time information, position description information and attitude description information in the carrier pose data to obtain the carrier motion state data; S22: Based on the acquisition time information corresponding to the acoustic frame sequence and the pose time information corresponding to the carrier motion state data, perform time alignment processing on the range and orientation observation data and the carrier motion state data to obtain frame pose association data corresponding to each acoustic frame; S23: Based on the frame pose association data, coordinate expression processing is performed on the position description information and attitude description information corresponding to each acoustic frame to obtain the spatial pose data corresponding to each acoustic frame.

[0041] It should be noted that: pose time information refers to the acquisition or recording time corresponding to the carrier pose data, used to match the acquisition time information of the acoustic frame; position description information refers to the representation information of the spatial position of the carrier during the acquisition of the acoustic frame; attitude description information refers to the attitude representation information of the carrier such as orientation, pitch, roll, or heading during the acquisition of the acoustic frame; carrier motion state data refers to the carrier motion representation data formed after parsing the time, position, and attitude content in the carrier pose data; time alignment processing refers to the process of matching or associating the acoustic observation data with the carrier motion state at the corresponding moment based on the acquisition time information of the acoustic frame and the pose time information of the carrier pose data; frame pose association data refers to the data formed after establishing an association between the acoustic frame and the carrier motion state at the corresponding acquisition moment; coordinate expression processing refers to the process of converting the position description information and attitude description information corresponding to the acoustic frame into a data expression form that can represent the spatial position and attitude relationship of the acoustic frame.

[0042] In practice, the carrier's pose data is first acquired during the acquisition of a single forward-looking sonar acoustic frame sequence. This pose data is then analyzed to extract pose time information, position description information, and attitude description information. The pose time information characterizes the acquisition time of the carrier pose data, the position description information characterizes the carrier's position in space, and the attitude description information characterizes the carrier's orientation at the corresponding acquisition time. By processing this information, carrier motion state data corresponding to the continuous motion process of the carrier can be formed, providing a foundation for subsequently associating acoustic frames with the carrier's spatial state.

[0043] Furthermore, based on the acquisition time information of each acoustic frame in the acoustic frame sequence, the range and orientation observation data corresponding to each acoustic frame are time-aligned with the carrier motion state data. Specifically, based on the acquisition time of the acoustic frame, the carrier motion state with matching or adjacent times can be determined in the carrier motion state data, and associated with the corresponding acoustic frame to obtain frame pose association data. When the acquisition time of the acoustic frame and the acquisition time of the carrier pose are not completely consistent, the motion states of adjacent carriers can be matched or estimated according to the time sequence to determine the carrier position and attitude corresponding to the acoustic frame. Subsequently, based on the frame pose association data, the position description information and attitude description information corresponding to each acoustic frame are processed into coordinate representation to obtain the spatial pose data corresponding to each acoustic frame.

[0044] By analyzing the pose time information, position description information, and attitude description information in the carrier pose data, the basic motion state of the carrier during the acoustic frame acquisition process can be obtained. By aligning the acquisition time information of the acoustic frames with the pose time information of the carrier motion data, an accurate correlation can be established between the range and azimuth observation data and the carrier's position and attitude at the corresponding moment. Further, coordinate processing is used to generate spatial pose data corresponding to each acoustic frame, giving the target observation information in different acoustic frames clear spatial position and attitude constraints. Therefore, the above steps can reduce the spatial correlation error caused by the asynchrony between acoustic observation data and carrier pose data, providing an accurate pose basis for subsequent determination of relative pose relationships and cross-frame 3D reconstruction, thereby helping to improve the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0045] This embodiment acquires a sequence of acoustic frames continuously collected by a single forward-looking sonar, and converts the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. Based on the acquisition time information corresponding to the acoustic frame sequence, the range and azimuth observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame. Based on the spatial pose data, the relative pose relationship between different acoustic frames is determined, and the target frame group is determined from the acoustic frame sequence according to the relative pose relationship. Based on the range and azimuth observation data corresponding to the target frame group, cross-frame corresponding points are correlated, and the cross-frame corresponding points are geometrically filtered according to the relative pose relationship to obtain valid corresponding point data. Based on the valid corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data. This embodiment first converts target observation information in the acoustic frame sequence into range and azimuth observation data, providing a basis for spatial computation. Then, based on acquisition time information, the range and azimuth observation data is correlated with the carrier pose data to obtain spatial pose data corresponding to each acoustic frame, providing a basis for spatial correlation of observation information in different acoustic frames. Subsequently, relative pose relationships are determined based on the spatial pose data, and target frame groups are identified accordingly, ensuring that the acoustic frames participating in the reconstruction have relative observation relationships that can be used for cross-frame constraints. Further, cross-frame corresponding point correlation is performed based on the target frame groups, and geometric screening is conducted in conjunction with relative pose relationships to reduce the number of corresponding points that do not conform to inter-frame spatial relationships from participating in the solution. Finally, the altitude-angle parameter of the same target point in different acoustic frames is used as a parameter to solve for spatial consistency, obtaining three-dimensional coordinate data and generating three-dimensional reconstruction results. Thus, through the coordinated operation of range and azimuth observation conversion, pose correlation, frame group determination, corresponding point screening, and altitude-angle parameter solving, the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar is improved.

[0046] Based on the second embodiment described above, a third embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar is proposed in this application. Please refer to... Figure 3 , Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in this application.

[0047] In this embodiment, step S3 includes: S31: Based on the spatial pose data, determine the reference acoustic frame and candidate acoustic frame to be compared from the acoustic frame sequence, and extract the first spatial pose data corresponding to the reference acoustic frame and the second spatial pose data corresponding to the candidate acoustic frame. S32: Based on the first spatial pose data and the second spatial pose data, perform inter-frame pose transformation analysis to determine the relative rotation relationship and relative translation relationship between the reference acoustic frame and the candidate acoustic frame, and obtain the relative pose relationship based on the relative rotation relationship and the relative translation relationship; S33: Based on the relative pose relationship, determine the observation baseline state between the reference acoustic frame and the candidate acoustic frame, and determine the reference acoustic frame and candidate acoustic frame that meet the preset observation conditions as the target frame group.

[0048] It should be noted that the reference acoustic frame refers to the acoustic frame used as a reference object during inter-frame comparison; the candidate acoustic frame refers to the acoustic frame selected from the acoustic frame sequence and used for pose comparison with the reference acoustic frame; the first spatial pose data refers to the spatial position and attitude data corresponding to the reference acoustic frame; the second spatial pose data refers to the spatial position and attitude data corresponding to the candidate acoustic frame; inter-frame pose transformation analysis refers to the process of determining the spatial transformation relationship between two frames based on the spatial pose data corresponding to the two frames; the relative rotation relationship refers to the attitude change relationship of the candidate acoustic frame relative to the reference acoustic frame; the relative translation relationship refers to the position change relationship of the candidate acoustic frame relative to the reference acoustic frame; the observation baseline state refers to the observation position difference state between the reference acoustic frame and the candidate acoustic frame caused by the carrier motion; and the preset observation conditions refer to the conditions used to determine whether two acoustic frames are suitable for participating in subsequent cross-frame reconstruction.

[0049] Specifically, in implementation, based on the spatial pose data corresponding to each acoustic frame, one frame is selected from the acoustic frame sequence as the reference acoustic frame, and acoustic frames acquired in subsequent or adjacent acquisition phases are selected as candidate acoustic frames. Then, the first spatial pose data corresponding to the reference acoustic frame and the second spatial pose data corresponding to the candidate acoustic frames are extracted, enabling subsequent analysis of the spatial relationship between the two frames from both position and orientation perspectives.

[0050] Furthermore, based on the first and second spatial pose data, inter-frame pose transformation analysis is performed to determine the pose and position changes of the candidate acoustic frame relative to the reference acoustic frame, thereby obtaining the relative rotation and relative translation relationships, which in turn form the relative pose relationship. Then, based on the relative pose relationship, the observation baseline state between the reference acoustic frame and the candidate acoustic frame is determined. When the observation position difference and pose change between the two frames meet the preset observation conditions, the reference acoustic frame and the candidate acoustic frame are identified as the target frame group; when the preset observation conditions are not met, the two frames are not used as the target frame group for subsequent cross-frame reconstruction.

[0051] By identifying the reference acoustic frame and candidate acoustic frames from the acoustic frame sequence and extracting their corresponding first and second spatial pose data, a clear data object can be provided for inter-frame spatial relationship analysis. The relative rotation and translation relationships obtained through inter-frame pose transformation analysis can accurately characterize the relative pose relationships between different acoustic frames. Furthermore, based on the relative pose relationships, the observation baseline state is determined, and only acoustic frames that meet preset observation conditions are identified as the target frame group. This reduces the participation of acoustic frames with insufficient spatial variation or unsuitable observation relationships in subsequent reconstruction. Therefore, this step provides a more reliable frame group basis for cross-frame corresponding point association and spatial consistency solutions, helping to improve the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0052] Based on the second embodiment described above, in this embodiment, step S4 includes: S41: Based on the target observation area corresponding to each acoustic frame in the target frame group, extract the observation points to be associated from the range and azimuth observation data corresponding to the target frame group, and perform cross-frame matching processing on the observation points to be associated in different acoustic frames to obtain cross-frame corresponding point data. S42: Based on the relative pose relationship, perform spatial mapping processing on the corresponding observation points in the cross-frame corresponding point data located in different acoustic frames to obtain the geometric association representation data corresponding to the cross-frame corresponding point data; S43: Based on the geometric correlation characterization data, the corresponding observation points in the cross-frame corresponding point data are screened for horizontal and height deviations, and the cross-frame corresponding point data that meets the preset geometric consistency conditions are determined as the valid corresponding point data.

[0053] It should be noted that the target observation area refers to the effective observation area in the acoustic frame corresponding to the underwater target to be reconstructed, which can be used to limit the processing range of cross-frame matching; the observation points to be associated refer to the observation points extracted from the range and orientation observation data corresponding to the target observation area, which are to be used to establish a correspondence between different acoustic frames; cross-frame matching processing refers to matching the observation points to be associated between different acoustic frames of the target frame group to determine the observation points corresponding to the same target point or the same local structure in different acoustic frames; cross-frame corresponding point data refers to the set of corresponding points formed after cross-frame matching processing; spatial mapping processing refers to the process of converting the corresponding observation points under different acoustic frames to a comparable spatial relationship for analysis based on the relative pose relationship; geometric association representation data refers to the data used to represent the spatial position relationship, horizontal deviation relationship, and height deviation relationship of cross-frame corresponding points; horizontal deviation refers to the positional difference of cross-frame corresponding points in the horizontal observation plane; height deviation refers to the positional difference of cross-frame corresponding points in the height direction; preset geometric consistency conditions refer to the screening conditions used to determine whether cross-frame corresponding points meet the inter-frame spatial geometric relationship.

[0054] In practice, for the identified target frame group, the observation points to be associated are first extracted from the range and azimuth observation data corresponding to the target frame group based on the target observation area in each acoustic frame. Since the target observation area can limit the acoustic response range of the target to be reconstructed, extracting the observation points to be associated within this area can reduce the influence of background reverberation, irrelevant structures, or invalid water bodies on the matching process. Subsequently, cross-frame matching processing is performed on the observation points to be associated in different acoustic frames within the target frame group, establishing a correspondence between observation points corresponding to the same underwater target point or the same local structure of the target in different acoustic frames, thereby obtaining cross-frame corresponding point data.

[0055] Furthermore, based on the relative pose relationships corresponding to the target frame group, spatial mapping processing is performed on the corresponding observation points in the cross-frame corresponding point data located in different acoustic frames, enabling geometric judgment of the corresponding observation points in different acoustic frames within a unified or comparable spatial relationship. Then, geometric association representation data is formed based on the spatial mapping processing results, and horizontal and vertical deviations of the cross-frame corresponding points are filtered based on this geometric association representation data. When the deviations of the cross-frame corresponding points in the horizontal position and vertical direction meet the preset geometric consistency conditions, the cross-frame corresponding point is retained as valid corresponding point data; when its deviation does not meet the preset geometric consistency conditions, it is discarded as an unreliable corresponding point.

[0056] By extracting the observation points to be associated within the target observation region corresponding to each acoustic frame in the target frame group, the cross-frame matching process can be focused on the observation range related to the target to be reconstructed, reducing the interference of irrelevant acoustic responses on the establishment of corresponding points. By spatially mapping the corresponding points across frames based on relative pose relationships, corresponding points under different acoustic frames can be compared under the condition of inter-frame spatial constraints. Furthermore, by filtering through horizontal and height deviations, cross-frame corresponding points that do not conform to spatial geometric relationships can be eliminated, retaining more reliable and effective corresponding point data. Thus, this step can reduce the impact of cross-frame mismatches on subsequent spatial consistency solutions, providing a more accurate basis for the generation of 3D coordinate data, thereby helping to improve the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0057] In this embodiment, step S5 includes: S51: Based on the effective corresponding point data, determine the distance and orientation observation data of the same target point in different acoustic frames, and determine the height-direction angle parameter of the same target point in different acoustic frames as the parameter to be determined; S52: Based on the range and orientation observation data, the parameters to be determined, and the relative pose relationship, construct the spatial consistency constraint of the same target point in different acoustic frames, and solve the constraint of the parameters to be determined to obtain the three-dimensional coordinate data corresponding to the target point; S53: Based on the spatial pose data, the three-dimensional coordinate data is transformed to a unified coordinate system, and the transformed three-dimensional coordinate data is fused to obtain the three-dimensional reconstruction result of the underwater target.

[0058] It should be noted that spatial consistency constraint refers to the constraint relationship that keeps the spatial position of the target point consistent, based on the observation results of the same target point in different acoustic frames and the relative pose relationship between the different acoustic frames; constraint solution refers to the process of solving for the parameters under the common constraints of range and azimuth observation data, the parameters to be solved, and the relative pose relationship; unified coordinate system refers to the spatial coordinate reference used to uniformly express the three-dimensional coordinate data obtained from different acoustic frames or different target frame groups; fusion processing refers to the process of merging, filtering, or integrating multiple three-dimensional coordinate data transformed to a unified coordinate system to form the overall spatial structure of the underwater target.

[0059] Specifically, in implementation, the range and azimuth observation data of the same target point in different acoustic frames are first determined based on valid corresponding point data. Since a single forward-looking sonar can directly obtain the range and azimuth information of a target point, but it is difficult to directly obtain the angle information of the target point in the height direction, the height-direction angle parameter of the same target point in different acoustic frames is used as a parameter to be determined. Subsequently, combining the range and azimuth observation data of the target point in different acoustic frames with the relative pose relationship corresponding to the target frame group, spatial consistency constraints are established between the same target point in different acoustic frames, enabling the observation results in different acoustic frames to be correlated and solved around the same spatial target point.

[0060] Furthermore, the height-angle parameters are constrained and solved based on spatial consistency constraints to determine the height-angle parameters of the same target point in different acoustic frames. This is then combined with range and azimuth observation data to obtain the corresponding three-dimensional coordinate data of the target point. Next, based on the spatial pose data corresponding to each acoustic frame, the three-dimensional coordinate data is transformed to a unified coordinate system, ensuring that the three-dimensional coordinate data obtained from different acoustic frames or different target frame groups have a consistent spatial representation basis. Finally, the transformed three-dimensional coordinate data is fused to form the three-dimensional reconstruction result of the underwater target.

[0061] By determining the range and azimuth observation data of the same target point in different acoustic frames based on effective corresponding point data, and using the altitude angle parameter as the parameter to be determined, altitude information that is difficult to obtain directly from a single forward-looking sonar can be incorporated into the solution process. By combining the range and azimuth observation data, the parameter to be determined, and the relative pose relationship to construct spatial consistency constraints, the observation results of the same target point in different acoustic frames can be constrained according to the inter-frame spatial relationship, thereby reducing the impact of missing altitude angles on 3D coordinate recovery. Furthermore, transforming the 3D coordinate data to a unified coordinate system and performing fusion processing allows for a unified expression and integration of 3D coordinate data generated from different acoustic frames or different target frame groups. Therefore, this step enhances the spatial consistency of the target point's 3D coordinate solution and the overall integrity of the reconstruction results, thus contributing to improving the accuracy of 3D reconstruction of underwater targets using a single forward-looking sonar.

[0062] This embodiment acquires a sequence of acoustic frames continuously collected by a single forward-looking sonar, and converts the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. Based on the acquisition time information corresponding to the acoustic frame sequence, the range and azimuth observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame. Based on the spatial pose data, the relative pose relationship between different acoustic frames is determined, and the target frame group is determined from the acoustic frame sequence according to the relative pose relationship. Based on the range and azimuth observation data corresponding to the target frame group, cross-frame corresponding points are correlated, and the cross-frame corresponding points are geometrically filtered according to the relative pose relationship to obtain valid corresponding point data. Based on the valid corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data. This embodiment first converts target observation information in the acoustic frame sequence into range and azimuth observation data, providing a basis for spatial computation. Then, based on acquisition time information, the range and azimuth observation data is correlated with the carrier pose data to obtain spatial pose data corresponding to each acoustic frame, providing a basis for spatial correlation of observation information in different acoustic frames. Subsequently, relative pose relationships are determined based on the spatial pose data, and target frame groups are identified accordingly, ensuring that the acoustic frames participating in the reconstruction have relative observation relationships that can be used for cross-frame constraints. Further, cross-frame corresponding point correlation is performed based on the target frame groups, and geometric screening is conducted in conjunction with relative pose relationships to reduce the number of corresponding points that do not conform to inter-frame spatial relationships from participating in the solution. Finally, the altitude-angle parameter of the same target point in different acoustic frames is used as a parameter to solve for spatial consistency, obtaining three-dimensional coordinate data and generating three-dimensional reconstruction results. Thus, through the coordinated operation of range and azimuth observation conversion, pose correlation, frame group determination, corresponding point screening, and altitude-angle parameter solving, the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar is improved.

[0063] Please refer to Figure 4 , Figure 4 This is a schematic diagram of the sonar coordinate system in one embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application. Figure 4 As shown, forward-looking sonar serves as the primary sensor for underwater target or scene perception, acquiring echo imaging data within a certain field of view in front of the sonar. The forward-looking sonar transmits acoustic pulse signals to the water body ahead via a transducer. These acoustic pulses propagate through the water and generate reflected echoes when they encounter fish, pool walls, nets, seabed, obstacles, or other underwater target surfaces. The sonar receiver receives these reflected echoes and generates a sonar image based on the echo arrival time, beam orientation, and echo intensity.

[0064] Specifically, after a sonar emits a sound pulse, if a reflected echo from the target is received in a certain direction, the distance between the target and the sonar can be calculated based on the propagation time of the sound wave from emission to return. This distance can be expressed as:

[0065] in, Indicates the first The distance corresponding to each echo cell This indicates the speed at which sound waves travel in water. This represents the time it takes for a sound wave to travel from emission to reception. Since the sound wave propagation process includes two stages—from the sonar to the target and from the target back to the sonar—the distance needs to be divided by 2 when calculating the distance.

[0066] Under ideal three-dimensional acoustic observation conditions, if the sonar can simultaneously obtain the distance to the target point... Azimuth and pitch angle The three-dimensional coordinates of the target point in the sonar local coordinate system can be expressed as:

[0067] in, This represents the three-dimensional coordinates of the target point in the sonar coordinate system. , , These represent the forward, lateral, and altitude coordinates of the target point in the sonar local coordinate system, respectively.

[0068] However, conventional forward-looking imaging sonar typically only obtains range, azimuth, and echo intensity information during actual operation, but not complete elevation information. In other words, forward-looking sonar compresses the echoes of underwater targets or scenes in real three-dimensional space into a two-dimensional range-azimuth imaging plane, forming a two-dimensional sonar image with range and azimuth as the primary coordinates and echo intensity as the pixel value. Therefore, a single frame of forward-looking sonar image can reflect the spatial distribution of the target within the range-azimuth plane, but the target's true position in the height direction remains uncertain.

[0069] Forward-looking sonar images are typically distributed in a fan-shaped or polar coordinate format. One direction corresponds to the range cell within the sonar's measurement range, and the other direction corresponds to the azimuth cell within the sonar's horizontal field of view. The image pixel values ​​correspond to the acoustic echo intensity at the corresponding location. Due to the influence of factors such as water attenuation, multipath reflection, reverberation noise, target surface morphology, incident angle, and obstruction relationships during underwater sound wave propagation, forward-looking sonar images often exhibit phenomena such as blurred boundaries, strong reflective bright spots, acoustic shadow regions, speckle noise, and background reverberation.

[0070] In aquaculture scenarios, fish bodies, pond walls, nets, aquaculture facilities, and underwater structures can all generate echo responses of varying intensities in forward-looking sonar images. Compared to underwater optical cameras, forward-looking sonar does not rely on natural light or artificial illumination and can acquire target echo information in turbid waters, low-light environments, and under conditions where visible light imaging is limited. Therefore, it is more suitable for complex underwater environments such as aquaculture ponds, net cages, marine ranches, and AUV underwater inspections.

[0071] Based on the aforementioned imaging mechanism, it is known that a single forward-looking sonar possesses strong adaptability to underwater environments, but its single-frame images suffer from a lack of height information. To address this issue, this embodiment utilizes a sequence of sonar images continuously acquired by a single forward-looking sonar during AUV movement, and combines this with the AUV's position and attitude information at each sonar acquisition moment to transform the sonar observation data acquired at different times into a unified three-dimensional coordinate system. Through time synchronization, pose correlation, spatial coordinate transformation, and point cloud fusion of multiple frames of sonar data, three-dimensional reconstruction of underwater targets or scenes based solely on a single forward-looking sonar is achieved.

[0072] In this embodiment, the overall process includes the following steps: Step 1: Acquire the raw sonar data stream continuously collected by a single forward-looking sonar, and generate a two-dimensional sonar image based on the distance sampling information, azimuth information, and echo intensity information; Step 2: Based on the pixel coordinates of the sonar image, the sonar range, and the azimuth array, convert the target pixel into a range-azimuth observation. Step 3: Obtain the position and attitude information of the carrier at the time of sonar image acquisition, and obtain the sonar pose corresponding to each frame of sonar image by aligning with the timestamp. Step 4: Calculate the relative rotation and translation between the two frames based on the sonar poses corresponding to the two sonar images, and select the effective sonar frame pair according to the preset baseline conditions. Step 5: Perform cross-frame matching within the target area of ​​the effective sonar frame pair to obtain the corresponding pixel points, and convert the corresponding pixel points into the corresponding range-azimuth observations; Step 6: Perform geometric pre-screening on the matching points to remove mismatched points that obviously do not conform to the spatial pose relationship between the two frames; Step 7: The elevation angle of the matching point in the two frames of sonar observations is used as an unknown variable, and the spatial consistency residual is constructed by combining the relative rotation and translation relationship between the two frames. Step 8: Solve for the optimal pitch angle by minimizing the spatial consistency residual, pitch angle consistency constraint, and pitch angle magnitude constraint, and calculate the three-dimensional coordinates of the matching point; Step 9: Transform the 3D points to the world coordinate system and fuse the 3D point clouds generated by multiple consecutive sonar frames to output the 3D reconstruction results of the underwater target or scene.

[0073] In one embodiment, the pitch angles corresponding to the two observation points are solved by minimizing the spatial consistency residuals:

[0074] in, This represents the pitch angle consistency constraint weight, used to constrain the pitch angle estimates of the same target point in two frames to maintain reasonable consistency. This represents the pitch angle amplitude constraint weight, used to suppress unreasonable large pitch angle solutions.

[0075] In the actual solution process, a search range can be set for the pitch angle. At the same time, unreasonable three-dimensional solutions can be eliminated by combining distance range constraints, forward ray constraints, minimum baseline constraints, and reconstruction residual constraints.

[0076] After obtaining the optimal pitch angle, the three-dimensional coordinates of the target point in the reference frame sonar coordinate system can be calculated:

[0077] Then, based on the sonar pose in the reference frame, transform this 3D point to the world coordinate system:

[0078] in, This represents the three-dimensional coordinates of the i-th target point in the world coordinate system.

[0079] Please see Figures 5-7 , Figure 5 This is a schematic diagram of the three-dimensional reconstruction result of a lake nearshore scene in one embodiment of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in this application; Figure 6 This is a schematic diagram of the three-dimensional reconstruction result of a water tank test scene in one embodiment of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in this application; Figure 7 This is a real-world scene diagram of a water tank test in one embodiment of the underwater target 3D reconstruction method based on a single forward-looking sonar in this application.

[0080] like Figure 5 As shown, during the experiment in the nearshore waters of a lake, a single forward-looking sonar continuously acquired acoustic frame sequences of the target area. Combined with the carrier's pose data during the acquisition process, pose correlation, cross-frame corresponding point filtering, and spatial consistency solving were performed on the target observation information in different acoustic frames, thereby obtaining a three-dimensional reconstruction result of the nearshore target area of ​​the lake in a unified coordinate system. This reconstruction result reflects the spatial distribution characteristics of the nearshore area, indicating that the method proposed in this application is applicable to single-forward-looking sonar three-dimensional reconstruction scenarios in natural water environments.

[0081] Please refer to Figure 6-7During the pool test, a single forward-looking sonar continuously observes the internal structure or target area of ​​the pool, and generates corresponding three-dimensional coordinate data based on the acoustic frame sequence, acquisition time information, and carrier pose data. By transforming the three-dimensional coordinate data obtained from different acoustic frames or different target frame groups into a unified coordinate system and performing fusion processing, a three-dimensional reconstruction result of the pool scene can be formed. This reconstruction result can characterize the spatial structural features of the pool wall, bottom, or the target under test, indicating that the method of this application can also obtain stable three-dimensional reconstruction results in a regular underwater test environment.

[0082] This application also provides an underwater target 3D reconstruction device based on a single forward-looking sonar. Please refer to... Figure 8 , Figure 8 This is a schematic diagram of the module structure of an underwater target 3D reconstruction device based on a single forward-looking sonar according to an embodiment of this application. The underwater target 3D reconstruction device based on a single forward-looking sonar includes: The information conversion module 501 is used to acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. The association processing module 502 is used to perform association processing on the range and orientation observation data and the carrier pose data based on the acquisition time information corresponding to the acoustic frame sequence, so as to obtain the spatial pose data corresponding to each acoustic frame. The target frame group module 503 is used to determine the relative pose relationship between different acoustic frames based on the spatial pose data, and to determine the target frame group from the acoustic frame sequence according to the relative pose relationship. The geometric filtering module 504 is used to associate cross-frame corresponding points based on the range and orientation observation data corresponding to the target frame group, and to perform geometric filtering on the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data. The 3D reconstruction module 505 is used to solve for spatial consistency by taking the height-angle parameter of the same target point in different acoustic frames as the parameter to be solved based on the effective corresponding point data and the relative pose relationship, so as to obtain the 3D coordinate data corresponding to the target point, and generate the 3D reconstruction result of the underwater target based on the 3D coordinate data.

[0083] The underwater target 3D reconstruction device based on a single forward-looking sonar provided in this application adopts the underwater target 3D reconstruction method based on a single forward-looking sonar in the above embodiments, and can solve the technical problem of how to improve the accuracy of underwater target 3D reconstruction based on a single forward-looking sonar. Compared with the prior art, the beneficial effects of the underwater target 3D reconstruction device based on a single forward-looking sonar provided in this application are the same as the beneficial effects of the underwater target 3D reconstruction method based on a single forward-looking sonar provided in the above embodiments, and other technical features in the underwater target 3D reconstruction device based on a single forward-looking sonar are the same as the features disclosed in the methods of the above embodiments, and will not be repeated here.

[0084] This application provides an underwater target 3D reconstruction device based on a single forward-looking sonar. The underwater target 3D reconstruction device based on a single forward-looking sonar includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the underwater target 3D reconstruction method based on a single forward-looking sonar in the above embodiments.

[0085] The following is for reference. Figure 9 , Figure 9 This is a schematic diagram of the hardware operating environment of the underwater target 3D reconstruction method based on a single forward-looking sonar in the embodiments of this application. It shows a schematic diagram of the structure of the underwater target 3D reconstruction device based on a single forward-looking sonar suitable for implementing the embodiments of this application. Figure 9 The underwater target 3D reconstruction device based on a single forward-looking sonar shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0086] like Figure 9As shown, the underwater target 3D reconstruction device based on a single forward-looking sonar may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the underwater target 3D reconstruction device based on the single forward-looking sonar. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the single forward-looking sonar-based underwater target 3D reconstruction equipment to exchange data wirelessly or via wired communication with other devices. Although the figure shows a single forward-looking sonar-based underwater target 3D reconstruction equipment with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0087] In particular, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. When the computer program is executed by the processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0088] The underwater target 3D reconstruction device based on a single forward-looking sonar provided in this application, employing the underwater target 3D reconstruction method based on a single forward-looking sonar in the above embodiments, can solve the technical problem of how to improve the accuracy of underwater target 3D reconstruction using a single forward-looking sonar. Compared with the prior art, the beneficial effects of the underwater target 3D reconstruction device based on a single forward-looking sonar provided in this application are the same as those of the underwater target 3D reconstruction method based on a single forward-looking sonar provided in the above embodiments, and other technical features in this underwater target 3D reconstruction device based on a single forward-looking sonar are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0089] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0090] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0091] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the underwater target three-dimensional reconstruction method based on a single forward-looking sonar in the above embodiments.

[0092] The aforementioned computer-readable storage medium carries one or more programs that, when executed by a single forward-looking sonar-based underwater target 3D reconstruction device, cause the single forward-looking sonar-based underwater target 3D reconstruction device to: acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence; perform correlation processing on the range and azimuth observation data and the carrier pose data based on the acquisition time information corresponding to the acoustic frame sequence to obtain the spatial pose data corresponding to each acoustic frame; and based on... Spatial pose data determines the relative pose relationships between different acoustic frames, and target frame groups are determined from the acoustic frame sequence based on these relationships. Cross-frame corresponding points are associated based on the range and azimuth observation data corresponding to the target frame groups, and geometric filtering is performed on these cross-frame corresponding points according to the relative pose relationships to obtain valid corresponding point data. Based on the valid corresponding point data and the relative pose relationships, the elevation-angle parameter of the same target point in different acoustic frames is used as a parameter to be solved for spatial consistency, obtaining the three-dimensional coordinate data corresponding to the target point. Based on the three-dimensional coordinate data, a three-dimensional reconstruction result of the underwater target is generated. Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer through any type of network—including a local area network (LAN) or a wide area network (WAN)—or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0093] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0094] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0095] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described underwater target 3D reconstruction method based on a single forward-looking sonar. This solves the technical problem of how to improve the accuracy of 3D underwater target reconstruction using a single forward-looking sonar. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the underwater target 3D reconstruction method based on a single forward-looking sonar provided in the above embodiments, and will not be repeated here.

[0096] This application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for three-dimensional reconstruction of underwater targets based on a single forward-looking sonar.

[0097] The computer program product provided in this application can solve the technical problem of how to improve the accuracy of three-dimensional reconstruction of underwater targets using a single forward-looking sonar. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the three-dimensional reconstruction method of underwater targets based on a single forward-looking sonar provided in the above embodiments, and will not be repeated here.

[0098] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for three-dimensional reconstruction of underwater targets based on a single forward-looking sonar, characterized in that, The method includes: Acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. Based on the acquisition time information corresponding to the acoustic frame sequence, the range and orientation observation data and the carrier pose data are correlated to obtain the spatial pose data corresponding to each acoustic frame. The relative pose relationship between different acoustic frames is determined based on the spatial pose data, and the target frame group is determined from the acoustic frame sequence according to the relative pose relationship. Based on the range and orientation observation data corresponding to the target frame group, cross-frame corresponding points are associated, and the cross-frame corresponding points are geometrically filtered according to the relative pose relationship to obtain valid corresponding point data. Based on the effective corresponding point data and the relative pose relationship, the height-angle parameter of the same target point in different acoustic frames is used as the parameter to be solved for spatial consistency, so as to obtain the three-dimensional coordinate data corresponding to the target point, and the three-dimensional reconstruction result of the underwater target is generated based on the three-dimensional coordinate data.

2. The method as described in claim 1, characterized in that, The step of acquiring a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and converting the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence, includes: The raw sonar data stream output by the single forward-looking sonar during continuous acquisition is obtained, and the distance sampling information, azimuth sampling information, echo intensity information and acquisition time information in the raw sonar data stream are analyzed to obtain continuous sonar acquisition data. Based on the range sampling information, azimuth sampling information, and echo intensity information in the continuous sonar acquisition data, imaging mapping processing is performed to generate the acoustic frame sequence with range direction and azimuth direction as coordinate dimensions and echo intensity as pixel representation. Based on the sonar range information, azimuth sampling information and pixel position relationship corresponding to the acoustic frame sequence, coordinate mapping processing is performed on the target observation information in the acoustic frame sequence to obtain the range and azimuth observation data corresponding to the target observation information.

3. The method as described in claim 1, characterized in that, The step of correlating the range and orientation observation data with the carrier pose data based on the acquisition time information corresponding to the acoustic frame sequence to obtain the spatial pose data corresponding to each acoustic frame includes: The carrier pose data corresponding to the acquisition of the acoustic frame sequence by the single forward-looking sonar is obtained, and the pose time information, position description information and attitude description information in the carrier pose data are parsed to obtain the carrier motion state data. Based on the acquisition time information corresponding to the acoustic frame sequence and the pose time information corresponding to the carrier motion state data, the distance and orientation observation data and the carrier motion state data are time-aligned to obtain frame pose association data corresponding to each acoustic frame. Based on the frame pose association data, coordinate representation processing is performed on the position description information and attitude description information corresponding to each acoustic frame to obtain the spatial pose data corresponding to each acoustic frame.

4. The method as described in claim 1, characterized in that, The step of determining the relative pose relationship between different acoustic frames based on the spatial pose data, and determining the target frame group from the acoustic frame sequence according to the relative pose relationship, includes: Based on the spatial pose data, a reference acoustic frame and a candidate acoustic frame to be compared are determined from the acoustic frame sequence, and the first spatial pose data corresponding to the reference acoustic frame and the second spatial pose data corresponding to the candidate acoustic frame are extracted. Based on the first spatial pose data and the second spatial pose data, inter-frame pose transformation analysis is performed to determine the relative rotation relationship and relative translation relationship between the reference acoustic frame and the candidate acoustic frame, and the relative pose relationship is obtained based on the relative rotation relationship and the relative translation relationship. Based on the relative pose relationship, the observation baseline state between the reference acoustic frame and the candidate acoustic frame is determined, and the reference acoustic frame and candidate acoustic frame that meet the preset observation conditions are determined as the target frame group.

5. The method as described in claim 1, characterized in that, The step of associating cross-frame corresponding points based on the range and azimuth observation data corresponding to the target frame group, and geometrically filtering the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data includes: Based on the target observation area corresponding to each acoustic frame in the target frame group, the observation points to be associated are extracted from the range and azimuth observation data corresponding to the target frame group, and cross-frame matching processing is performed on the observation points to be associated in different acoustic frames to obtain cross-frame corresponding point data. Based on the relative pose relationship, spatial mapping processing is performed on the corresponding observation points in the cross-frame corresponding point data located in different acoustic frames to obtain the geometric association representation data corresponding to the cross-frame corresponding point data. Based on the geometric correlation characterization data, the corresponding observation points in the cross-frame corresponding point data are filtered for horizontal and height deviations, and the cross-frame corresponding point data that meet the preset geometric consistency conditions are determined as the valid corresponding point data.

6. The method as described in claim 1, characterized in that, The step of obtaining the three-dimensional coordinate data corresponding to the target point by using the height-direction angle parameter of the same target point in different acoustic frames as the parameter to be solved for spatial consistency based on the effective corresponding point data and the relative pose relationship, and generating the three-dimensional reconstruction result of the underwater target based on the three-dimensional coordinate data, includes: Based on the effective corresponding point data, the distance and orientation observation data of the same target point in different acoustic frames are determined, and the height-direction angle parameter of the same target point in different acoustic frames is determined as the parameter to be determined; Based on the distance and orientation observation data, the parameters to be determined, and the relative pose relationship, a spatial consistency constraint for the same target point is constructed between different acoustic frames, and the parameters to be determined are constrained and solved to obtain the three-dimensional coordinate data corresponding to the target point. Based on the spatial pose data, the three-dimensional coordinate data is transformed to a unified coordinate system, and the transformed three-dimensional coordinate data is fused to obtain the three-dimensional reconstruction result of the underwater target.

7. A three-dimensional reconstruction device for underwater targets based on a single forward-looking sonar, characterized in that, The device includes: The information conversion module is used to acquire a sequence of acoustic frames continuously acquired by a single forward-looking sonar, and convert the target observation information in the acoustic frame sequence into range and azimuth observation data based on the imaging parameters corresponding to the acoustic frame sequence. The association processing module is used to perform association processing on the range and orientation observation data and the carrier pose data based on the acquisition time information corresponding to the acoustic frame sequence, so as to obtain the spatial pose data corresponding to each acoustic frame. The target frame group module is used to determine the relative pose relationship between different acoustic frames based on the spatial pose data, and to determine the target frame group from the acoustic frame sequence according to the relative pose relationship. The geometric filtering module is used to associate cross-frame corresponding points based on the distance and orientation observation data corresponding to the target frame group, and to perform geometric filtering on the cross-frame corresponding points according to the relative pose relationship to obtain valid corresponding point data. The 3D reconstruction module is used to solve for spatial consistency by taking the height-angle parameter of the same target point in different acoustic frames as the parameter to be solved based on the effective corresponding point data and the relative pose relationship, so as to obtain the 3D coordinate data corresponding to the target point, and generate the 3D reconstruction result of the underwater target based on the 3D coordinate data.

8. A computer device, characterized in that, The device includes: a memory, a processor, and a single forward-looking sonar-based underwater target 3D reconstruction program stored in the memory and executable on the processor, the single forward-looking sonar-based underwater target 3D reconstruction program being configured to implement the steps of the single forward-looking sonar-based underwater target 3D reconstruction method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a three-dimensional underwater target reconstruction program based on a single forward-looking sonar. When the single forward-looking sonar-based three-dimensional underwater target reconstruction program is executed by a processor, it implements the steps of the three-dimensional underwater target reconstruction method based on a single forward-looking sonar as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the underwater target three-dimensional reconstruction method based on a single forward-looking sonar as described in any one of claims 1 to 6.

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