A shipboard multi-beam swath point cloud registration method and system

Abstract

The application provides a shipborne multi-beam swath point cloud registration method and system, wherein the method comprises the following steps: acquiring a denoised channel point cloud as a first channel point cloud; extracting a navigation track point in the first channel point cloud; segmenting the first channel point cloud according to a turning angle of the navigation track point to obtain a plurality of swath segment point clouds; extracting a point set of an overlapping area between adjacent swath segment point clouds; constructing a correction value point cloud according to the point set of the overlapping area; constructing a correction TIN model of each swath segment according to the correction value point cloud; judging whether a plane position of a target swath segment point is inside a triangle in the TIN model; if yes, correcting an elevation value of the target swath segment point; and if no, not correcting the elevation value of the target swath segment point. The application can automatically match a layered phenomenon existing in point clouds in an overlapping area between different scanning swath segments, eliminate data errors, and provide precision guarantee for subsequent classification processing of the point clouds.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of surveying science and water transportation technology, and particularly relates to a shipborne multi-beam swath point cloud registration method and system. BACKGROUND

[0002] The shipborne multi-beam system can be used to obtain underwater topographic survey data. The shipborne multi-beam system scans the underwater topography to obtain strip-shaped swath point cloud data representing the topographic undulations, and the swath width is related to the water depth and the scanning opening angle. Generally, a plurality of swath scans along the direction of travel are required for a channel, and inspection swath scans perpendicular to the direction of travel are set at certain intervals, so that the complete underwater topography can be obtained, and the data preprocessing work is complex and important. Due to the influence of GNSS receiver, transducer, inertial navigation system and other system errors during data acquisition, the multi-beam system produces mismatching problems between swath point clouds, which causes obstacles to the later point cloud classification processing and underwater topographic modeling, and even causes serious consequences that the accuracy of the results does not meet the requirements. At present, the method of fitting a surface to correct all swaths uniformly is adopted, which will ignore the influence of local data instability, causing gross errors in the matching between swaths. SUMMARY

[0003] The present application provides a shipborne multi-beam swath point cloud registration method and system to overcome the deficiencies in the prior art.

[0004] In a first aspect, the present application provides a shipborne multi-beam swath point cloud registration method, characterized in that it comprises:

[0005] obtaining the denoised channel point cloud as the first channel point cloud;

[0006] extracting the track points in the first channel point cloud;

[0007] segmenting the first channel point cloud according to the turning angles of the track points to obtain a plurality of swath segment point clouds;

[0008] extracting the point set of the overlapping region between adjacent swath segment point clouds;

[0009] constructing a correction value point cloud according to the point set of the overlapping region;

[0010] constructing a correction TIN model of each swath segment according to the correction value point cloud;

[0011] judging whether the position of the point of the target swath segment is inside the triangle in the TIN model;

[0012] if yes, correcting the elevation value of the point in the target swath segment;

[0013] if no, not correcting the elevation value of the point in the target swath segment.

[0014] Further, the extracting the sailing trajectory points in the first fairway point cloud comprises:

[0015] obtaining a GPSTime field in the first fairway point cloud;

[0016] grouping the first fairway point clouds at the same time into a group;

[0017] sorting the points in the target group point cloud according to the elevation values, and taking the point with the largest elevation in the target group point cloud as a trajectory point of the target group point cloud;

[0018] traversing the trajectory points in all groups to obtain the sailing trajectory points in the first fairway point cloud.

[0019] Further, the segmenting the first fairway point cloud according to the turning angles of the sailing trajectory points to obtain a plurality of fairway segment point clouds comprises:

[0020] sorting the trajectory points in all groups according to the GPSTime, and taking the minimum value as a starting position;

[0021] taking three points in sequence from the sorted trajectory points, and calculating an angle value θ of an angle with the second point as a vertex according to the following formula:

[0022] θ = arccos ((a 2 +b 2 -c 2 ) / 2ab);

[0023] wherein a and b are lengths of two adjacent sides of the angle with the second point as a vertex, and c is a length of a side opposite to the second point;

[0024] taking the points with the angles greater than an angle threshold as inflection points;

[0025] taking two inflection points in sequence, and taking the point cloud between the two inflection points as a fairway segment point cloud.

[0026] Further, the extracting a point set in an overlapping area between adjacent fairway segment point clouds comprises:

[0027] constructing a KD tree index for the point cloud to be processed by fairway segment;

[0028] taking the target fairway segment point cloud as a target point set, and searching for each point in the target point set in two fairway segment point clouds according to a preset radius threshold;

[0029] in a case where both search results are not empty, determining the point being processed as an overlapping point;

[0030] Traverse the remaining flight strip section point cloud to obtain point set V1 and point set V2, and all overlapping points are taken as the point set of the overlapping region between adjacent flight strip section point clouds.

[0031] Further, the constructing the correction value point cloud according to the point set of the overlapping region comprises:

[0032] For each point position on the point set V1, search in the point set V1 with a target radius, and take the average height of all points in the target radius range as the height value h1 of the current point;

[0033] For the current point position, search in the point set V2 with a target radius, take the average height of all points in the target radius range as the height value h2 of the current point position, and take (h1+h2) / 2 as the average height value of the current point position;

[0034] A new spatial point is created for each point in the point set Vi, and when the point set Vi is traversed, all newly created spatial points are stored in the correction value point cloud S i , i is the flight strip section number; wherein the creation rule of the new spatial point is that the plane position (x, y) is consistent with the plane position of the corresponding point in the point set Vi, and the height value z takes the average height value of the corresponding point in the point set Vi minus the height value of the corresponding point;

[0035] The channel is divided into multiple channel blocks;

[0036] Traverse all flight strip sections in the same channel block to obtain the correction value point cloud of all flight strip sections in the same channel block;

[0037] Traverse all blocks of the channel to obtain the correction value point cloud NS i of the target flight strip section in the target block in the channel; N is the channel block number.

[0038] Further, the correcting the height value of the point in the target flight strip section comprises:

[0039] The height value of the point in the target flight strip section is calculated according to the following formula:

[0040] Z 改正 = Z 当前 +(Ax+By+D) / C;

[0041] Wherein, Z 改正 is the corrected height value of the point of the target flight strip section; Z 当前 is the height value of the point of the target flight strip section before correction; A, B and C are respectively three components of the normal vector of the triangular plane; and D is the distance from the origin to the triangular plane.

[0042] In the second aspect, the application provides a shipborne multi-beam flight strip point cloud registration system, comprising:

[0043] An acquisition module is configured to acquire the denoised channel point cloud as a first channel point cloud;

[0044] A first extraction module is configured to extract a navigation track point in the first channel point cloud;

[0045] A segmentation module is configured to segment the first channel point cloud according to a turning angle of the navigation track point to obtain a plurality of channel segment point clouds;

[0046] A second extraction module is configured to extract a point set in an overlapping region between adjacent channel segment point clouds;

[0047] A first construction module is configured to construct a correction value point cloud according to the point set in the overlapping region;

[0048] A second construction module is configured to construct a correction TIN model of each channel segment according to the correction value point cloud;

[0049] A judgment module is configured to judge whether a plane position of a point of a target channel segment is inside a triangle in the TIN model;

[0050] A first correction module is configured to correct an elevation value of the point in the target channel segment when the judgment module determines that the plane position of the point in the target channel segment is inside the triangle in the TIN model;

[0051] A second correction module is configured to not correct the elevation value of the point in the target channel segment when the judgment module determines that the plane position of the point in the target channel segment is not inside the triangle in the TIN model.

[0052] In a third aspect, the present application provides a computer device, comprising a processor and a memory; wherein the processor implements the steps of the shipborne multi-beam channel point cloud registration method of the first aspect when executing the computer program saved in the memory.

[0053] In a fourth aspect, the present application provides a computer readable storage medium for storing a computer program; the computer program implements the steps of the shipborne multi-beam channel point cloud registration method of the first aspect when executed by the processor.

[0054] The application provides a shipborne multi-beam navigation strip point cloud registration method and system, wherein the method comprises the following steps: acquiring a denoised navigation strip point cloud as a first navigation strip point cloud; extracting a navigation track point in the first navigation strip point cloud; segmenting the first navigation strip point cloud according to a turning angle of the navigation track point to obtain a plurality of navigation strip segment point clouds; extracting a point set in an overlapping area between adjacent navigation strip segment point clouds; constructing a correction value point cloud according to the point set in the overlapping area; constructing a correction TIN model of each navigation strip segment according to the correction value point cloud; judging whether a plane position of a point in a target navigation strip segment is inside a triangle in the TIN model; if yes, correcting an elevation value of the point in the target navigation strip segment; and if no, not correcting the elevation value of the point in the target navigation strip segment. The application can automatically match the layered phenomenon of the point cloud in the overlapping area between different scanning navigation strip segments, eliminate data errors, and provide precision guarantee for subsequent point cloud classification processing. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the present application, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0056] Figure 1 A flowchart of a shipborne multi-beam navigation strip point cloud registration method provided by the embodiment of the present application;

[0057] Figure 2 Another flowchart of a shipborne multi-beam navigation strip point cloud registration method provided by the embodiment of the present application;

[0058] Figure 3 A shipborne multi-beam point cloud data category display diagram provided by the embodiment of the present application;

[0059] Figure 4 A ship route track line schematic diagram provided by the embodiment of the present application;

[0060] Figure 5 A multi-beam point cloud navigation strip segment segmentation schematic diagram provided by the embodiment of the present application;

[0061] Figure 6 A multi-beam point cloud registration result local schematic diagram provided by the embodiment of the present application;

[0062] Figure 7 A structure schematic diagram of a shipborne multi-beam navigation strip point cloud registration system provided by the embodiment of the present application. DETAILED DESCRIPTION

[0063] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0064] In an embodiment, as shown in Figure 1 and Figure 2 , the embodiment of the present application provides a shipborne multi-beam swath point cloud registration method, comprising:

[0065] Step 101, obtaining the denoised channel point cloud as the first channel point cloud.

[0066] The collected multi-beam scanning point cloud data is as shown in Figure 3 , wherein the number of point clouds is 6682112, the point spacing is about 0.07m, and the density is about 300 points per square meter.

[0067] Exemplarily, this step comprises:

[0068] (1) Point cloud denoising based on distance statistics: for each point, the average distance to the surrounding 100 nearest neighbor points is calculated. Assuming that the obtained result is a Gaussian distribution, the distribution is determined by the mean and the standard deviation, then the points with the average distance outside 2 times the standard deviation can be considered as outliers and removed.

[0069] (2) Point cloud denoising based on number statistics: after step (1) processing, part of the sparse outliers can be removed. In order to remove a certain amount of noise cluster point clouds, here, a radius (for example, 0.5m) search is performed on each point. If the number of searched points is less than the preset number threshold (for example, 100), it is removed, otherwise, it should be retained. Here, the number threshold is set to 100 mainly because when a search radius of 0.5m is used, combined with the point cloud density, theoretically 235 points can be obtained, but considering that the density of the collected point cloud is inconsistent in different areas, therefore, the threshold of the search is set using 2 times the mean error.

[0070] (3) Obtaining the point cloud set to be processed: sequentially processing the experimental data by steps (1) and (2), the point cloud required for subsequent processing can be obtained.

[0071] Step 102, extracting the navigation track points in the first channel point cloud.

[0072] Exemplarily, this step comprises:

[0073] Obtaining the GPSTime field in the first channel point cloud.

[0074] The first track point cloud at the same time is divided into a group.

[0075] The points in the target group point cloud are sorted according to the elevation value, and the point with the maximum elevation in the target group point cloud is taken as the trajectory point of the target group point cloud.

[0076] The trajectory points in all groups are traversed to obtain the sailing trajectory points in the first track point cloud.

[0077] Step 103, segmenting the first track point cloud according to the turning angle of the sailing trajectory points to obtain a plurality of track segment point clouds.

[0078] Exemplarily, the step includes:

[0079] The trajectory points in all groups are sorted according to the GPS time, and the minimum value is taken as the starting position.

[0080] For the sorted trajectory points, any three points are taken in turn, and the angle value θ of the angle with the second point as the vertex is calculated according to the following formula:

[0081] θ = arccos ((a 2 +b 2 -c 2 ) / 2ab).

[0082] Wherein, a and b are the lengths of the adjacent two sides of the angle with the second point as the vertex; c is the opposite side length of the second point;

[0083] The point with an angle greater than the angle threshold is taken as the inflection point.

[0084] Any two inflection points are taken in turn, and the point cloud between the two inflection points is taken as a track segment point cloud.

[0085] For steps 102-103, as shown in Figure 4 , the points belonging to the trajectory line in the point cloud to be processed are extracted. The specific method is as follows: ① Point cloud grouping: according to the GPS time field in the input point cloud, the point cloud at the same time is divided into a group, and here, a total of 13051 groups are divided. ② Trajectory point judgment: for the point cloud after grouping in ①, the points in each group are sorted according to the elevation information, and the maximum elevation value is taken as the trajectory point in the current group. ③ Summary: after all groups are processed, all trajectory points in the input point cloud can be obtained, which constitute the trajectory line of the ship route.

[0086] As shown in Figure 5As shown, the input point cloud is segmented according to the size of the turning angle of the track point. The specific method is as follows: ① Determine the starting position: for the obtained track line, sort according to GPS time, and take the minimum value (for example, 361160305.00899982) as the starting position. ② Angle calculation: for the sorted track points in ①, take three points in turn, and calculate the size of the angle of the middle point. ③ Judgment of inflection point: when the angle value of a point is greater than the preset angle threshold (for example, 10°), it is considered that the turning angle of the ship at this point is large, and there may be a change in the heading. At this time, the current point is marked as an inflection point. After calculation, there are 7 inflection points. ④ Segmentation: after ③ processing, there may be a series of inflection points. According to the order, take two points in turn, and save the point cloud located in the current two points as a las file. After traversing all the inflection points, the segmentation of the point cloud is completed, and finally 8 segmented las files are obtained.

[0087] Step 104, extracting the point set of the overlapping region between the adjacent track segment point clouds.

[0088] Exemplarily, this step includes:

[0089] KD tree index is constructed for the point cloud to be processed per track segment.

[0090] The target track segment point cloud is taken as the target point set, and each point of the target point set is searched in the two track segment point clouds according to the preset radius threshold (for example, 0.1 m).

[0091] In the case that both search results are not empty, it is determined that the currently processed point is an overlapping point.

[0092] The remaining track segment point clouds are traversed, that is, the second track segment point cloud is processed in the same way to obtain point set V1 and point set V2, that is, the points marked as overlapping in the two extracted track segment point clouds are respectively stored in point set V1 and point set V2, and all overlapping points are taken as the point set of the overlapping region between adjacent track segment point clouds.

[0093] Step 105, constructing the correction value point cloud according to the point set of the overlapping region.

[0094] The average height difference dh between the overlapping points is calculated: for each point in point set V1, search in point set V1 with a target radius, and take the average height of all points within the target radius as the height value h1 of the current point.

[0095] Search for the current point in point set V2 with a target radius, and take the average height of all points within the target radius as the height value h2 of the current point, and take (h1+h2) / 2 as the average height value of the current point.

[0096] Construct the correction value point cloud of the overlapping area of the flight strips. After processing, each point in the point set V1 has an average elevation value attribute. Exemplarily, a new spatial point is created for each point in the point set Vi, and when the point set Vi is traversed, all the newly created spatial points are stored in the correction value point cloud S i , where i is the flight strip section number (the first flight strip i = 1, the second flight strip i = 2, and so on); S1 is the correction value point cloud created for the overlapping area of the first flight section and the second flight section.

[0097] The creation rule of the new spatial point is that the plane position (x, y) is consistent with the plane position of the corresponding point in the point set Vi, and the elevation value z is the average elevation value of the corresponding point in the point set Vi minus the elevation value of the corresponding point.

[0098] For example, the plane position (x, y) is consistent with the plane position of the corresponding point in the point set V1, and the elevation value z is the average elevation value of the corresponding point in the point set V1 minus the elevation value of the corresponding point. It should be noted that the point set V1 here represents the points in the first flight section in the overlapping data set to be processed. Similarly, the correction value point cloud S2 created for the overlapping area of the second flight section and the third flight section is obtained. If the first flight section has an overlapping area with another flight section, the above principle is continued to be processed, and the S1 data set is appended. According to the above method, all the flight sections in the same channel block are traversed, the correction values of all the flight sections in the same channel block are obtained, and the correction value point cloud is created (the first channel block N = 1, the second channel block N = 2, and so on). According to the above method, all the channel blocks are traversed, the correction values of all the flight sections in the channel block are obtained, and the correction value point cloud NS i is created.

[0099] The channel is divided into multiple channel blocks.

[0100] In this embodiment, the channel is divided into channel blocks according to the position from upstream to downstream of the channel, and the channel blocks are numbered. Then, the flight sections are arranged according to the channel blocks, and the flight sections are numbered from left to right according to the upstream to downstream direction, and the file names of the flight sections are named by adding the channel block number in front of the number. Finally, the block connection relationship of all the point clouds in the channel is established, and the channel division engineering file is formed. The river channel is about 450 m long, and the river channel is divided into 5 blocks at intervals of 100 m.

[0101] All the flight sections in the same channel block are traversed to obtain the correction value point cloud of all the flight sections in the same channel block.

[0102] All the channel blocks are traversed to obtain the correction value point cloud NS i of the target flight section in the target block in the channel; N is the channel block number.

[0103] Step 106, constructing a correction TIN model of each flight strip segment according to the correction value point cloud.

[0104] Step 107, judging whether the plane position of the point in the target flight strip segment is inside the triangle in the TIN model.

[0105] Step 108, if yes, correcting the elevation value of the point in the target flight strip segment.

[0106] Step 109, if no, not correcting the elevation value of the point in the target flight strip segment.

[0107] In steps 106-109, the creation sequence is from upstream to downstream of the channel block and from left to right of the flight strip, and one flight strip is corrected at a time. For the point in each flight strip, it is judged whether the plane position is inside a triangle in the TIN. The elevation value of the point in the target flight strip is calculated according to the following formula:

[0108] Z 改正 =Z 当前 +(Ax+By+D) / C.

[0109] Wherein, Z 改正 is the corrected elevation value of the point in the target flight strip; Z 当前 is the uncorrected elevation value of the point in the target flight strip; A, B and C are three components of the normal vector of the triangle plane; and D is the distance from the origin to the triangle plane. As shown in the formula, after the elevation values of all the multi-beam point clouds are corrected, the registration of the point cloud is completed. Figure 6

[0110] The embodiment of the application provides a shipborne multi-beam flight strip point cloud registration method, which can automatically match the layered phenomenon of the point cloud in the overlapping area between different scanning flight strip segments, eliminate data errors, and provide precision guarantee for subsequent classification processing of the point cloud.

[0111] Based on the same inventive concept, the embodiment of the application also provides a shipborne multi-beam flight strip point cloud registration system. Since the principle of solving the problem of the system is similar to the aforementioned shipborne multi-beam flight strip point cloud registration method, the implementation of the system can be referred to the implementation of the shipborne multi-beam flight strip point cloud registration method, and the repeated parts will not be described herein.

[0112] In another embodiment, the shipborne multi-beam flight strip point cloud registration system provided by the embodiment of the application, as shown in the formula, comprises: Figure 7 An acquisition module 10 is configured to acquire the channel point cloud after denoising as the first channel point cloud.

[0113] A first extraction module 20 is configured to extract the flight trajectory points in the first channel point cloud.

[0114]

[0115] ​​The segmentation module 30 is configured to segment the first track point cloud according to the turning angle of the navigation track point to obtain a plurality of track segment point clouds.

[0116] The second extraction module 40 is configured to extract a point set of an overlapping area between adjacent track segment point clouds.

[0117] The first construction module 50 is configured to construct a correction value point cloud according to the point set of the overlapping area.

[0118] The second construction module 60 is configured to construct a correction TIN model of each track segment according to the correction value point cloud.

[0119] The judgment module 70 is configured to judge whether the plane position of a point of a target track segment is inside a triangle in the TIN model.

[0120] The first correction module 80 is configured to correct the elevation value of the point in the target track segment when the judgment module determines that the plane position of the point in the target track segment is inside the triangle in the TIN model.

[0121] The second correction module 90 is configured to not correct the elevation value of the point in the target track segment when the judgment module determines that the plane position of the point in the target track segment is not inside the triangle in the TIN model.

[0122] The more specific working process of each module described above can refer to the corresponding content disclosed in the foregoing embodiments, and will not be described here.

[0123] In another embodiment, the present application provides a computer device comprising a processor and a memory; wherein the processor implements the steps of the shipborne multi-beam track point cloud registration method when executing the computer program stored in the memory.

[0124] The more specific process of the method described above can refer to the corresponding content disclosed in the foregoing embodiments, and will not be described here.

[0125] In another embodiment, the present application provides a computer readable storage medium for storing a computer program; the computer program is executed by a processor to implement the steps of the shipborne multi-beam track point cloud registration method.

[0126] The more specific process of the method described above can refer to the corresponding content disclosed in the foregoing embodiments, and will not be described here.

[0127] The various embodiments are described in the specification in a progressive manner, each embodiment focusing on different aspects of the other embodiments, and the same or similar parts between the various embodiments can be mutually referred to. For the system, device and storage medium disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0128] Those skilled in the art can clearly understand that the technology in the embodiments of the present application can be realized by means of software and necessary general hardware platforms. Based on such understanding, the technical solutions in the embodiments of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the method described in the various embodiments or some parts of the embodiments of the present application.

[0129] The present application has been described in detail in the above in combination with specific implementation manners and exemplary examples, but these descriptions cannot be understood as limitations of the present application. Those skilled in the art understand that the technical solutions and implementation manners of the present application can be variously replaced, modified or improved without departing from the spirit and scope of the present application, and these all fall within the scope of the present application. The protection scope of the present application is subject to the appended claims.

Claims

1. A shipborne multibeam flight strip point cloud registration method, characterized in that, include: Obtain the denoised channel point cloud as the first channel point cloud; Extract navigation trajectory points from the point cloud of the first channel, specifically including: Retrieve the GPSTime field from the point cloud of the first channel; Group the point clouds of the first channel located at the same time into one group; Sort the points in the target group point cloud according to their elevation values, and take the point with the highest elevation in the target group point cloud as the trajectory point of the target group point cloud. Traverse all the trajectory points in the group to obtain the navigation trajectory points in the first channel point cloud; The point cloud of the first channel is segmented based on the turning angle of the navigation trajectory points to obtain multiple channel segment point clouds, specifically including: Sort all trajectory points in the groups according to GPSTime, and take the minimum value as the starting position; For the sorted trajectory points, take any three points in sequence and calculate the angle value with the second point as the vertex using the following formula. θ : θ = arccos(( a 2 + b 2 - c 2 ) / 2 ab ); in, a and b These are the lengths of the two adjacent sides of the angle with the second point as its vertex; c The length of the side opposite the second point; Points with angles greater than the angle threshold are taken as inflection points; Take any two inflection points in sequence, and use the point cloud between the two inflection points as a flight strip segment point cloud; Extract the point set of the overlapping region between point clouds of adjacent flight strip segments; Construct a correction point cloud based on the point set of the overlapping region; Based on the point cloud of correction values, construct the corrected TIN model for each flight strip segment; Determine whether the plane position of the point in the target flight strip segment is inside the triangle in the TIN model; If so, correct the elevation values ​​of points within the target flight strip segment; If not, the elevation values ​​of points within the target flight zone segment will not be corrected.

2. The shipborne multibeam flight strip point cloud registration method according to claim 1, characterized in that, The extraction of point sets of overlapping regions between point clouds of adjacent flight strip segments includes: Construct a KD-tree index for each row-by-row segment of the point cloud to be processed; Using the target flight zone point cloud as the target point set, each point in the target point set is searched in the two flight zone point clouds according to a preset radius threshold. If both search results are not empty, the point being processed is determined to be an overlapping point; Traverse the remaining point cloud of the flight strip segment to obtain point set V1 and point set V2, and use all overlapping points as the point set of the overlapping area between adjacent flight strip point clouds.

3. The shipborne multibeam flight strip point cloud registration method according to claim 2, characterized in that, The construction of the correction point cloud based on the point set of the overlapping region includes: For each point in point set V1, search point set V1 with the target radius, and take the average elevation of all points within the target radius as the elevation value h1 of the current point; Search the current point on the point set V2 with the target radius, take the average elevation of all points within the target radius as the elevation value h2 of the current point, and take (h1+h2) / 2 as the average elevation value of the current point; For each point in the point set Vi, create a new spatial point. When the point set Vi has been traversed, store all the newly created spatial points in the correction value point cloud S. i In the diagram, i represents the flight strip segment number; the rules for creating new spatial points are as follows: the planar position (x, y) is consistent with the planar position of the corresponding point in the point set Vi, and the elevation value z is the average elevation value of the corresponding point in the point set Vi minus the elevation value of the corresponding point; The waterway is divided into sections, resulting in multiple waterway blocks; Traverse all strip segments within the same channel block to obtain the correction value point cloud of all strip segments within the same channel block; Traverse all blocks of the channel to obtain the correction value point cloud NS of the target flight strip segment in the target block within the channel. i N is the channel block number.

4. The shipborne multibeam flight strip point cloud registration method according to claim 1, characterized in that, The elevation values ​​of points within the target flight strip segment to be corrected include: Calculate the elevation values ​​of points within the target flight strip segment using the following formula: Z 改正 =Z 当前 +(Ax+By+D) / C; Among them, Z 改正 Z represents the point-corrected elevation value for the target flight strip segment. 当前 is the elevation value of the target flight strip segment before point correction; A, B, and C are the three components of the normal vector of the triangular plane; D is the distance from the origin to the triangular plane.

5. A shipborne multibeam flight strip point cloud registration system, used to perform the steps of the shipborne multibeam flight strip point cloud registration method according to any one of claims 1 to 4, characterized in that, include: The acquisition module is used to acquire the denoised channel point cloud as the first channel point cloud; The first extraction module is used to extract navigation trajectory points from the point cloud of the first channel. The segmentation module is used to segment the first channel point cloud according to the turning angle of the navigation trajectory points to obtain multiple channel segment point clouds. The second extraction module is used to extract the point set of the overlapping region between point clouds of adjacent flight strip segments; The first construction module is used to construct a correction point cloud based on the point set of the overlapping region; The second construction module is used to construct the corrected TIN model for each flight strip segment based on the point cloud of the corrected values. The judgment module is used to determine whether the plane position of the point of the target flight strip segment is inside the triangle in the TIN model; The first correction module is used to correct the elevation values ​​of points within the target flight strip when the judgment module determines that the plane position of the point in the target flight strip is inside the triangle in the TIN model. The second correction module is used to not correct the elevation values ​​of points within the target flight strip if the judgment module determines that the plane position of the point in the target flight strip is not inside the triangle in the TIN model.

6. A computer device, characterized in that, It includes a processor and a memory; wherein, when the processor executes the computer program stored in the memory, it implements the steps of the shipborne multibeam flight strip point cloud registration method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, Used to store computer programs; when executed by a processor, the computer programs implement the steps of the shipborne multibeam flight strip point cloud registration method according to any one of claims 1-4.

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