Method for updating a water depth of a channel and storage medium

Abstract

The application provides a method for updating a water depth of a channel and a storage medium, wherein the method first acquires discrete new sounding points containing coordinates, water depth values and time stamps in real time by loading a depth sounder on a ship; then generates a sounding surface by using a concave shell boundary extraction algorithm and an irregular triangle net interpolation algorithm; projects and registers the new generated sounding surface and an old version water depth surface in a point set form to obtain corresponding registered point pairs in space; processes the registered point pairs by using a Huber loss function and an iterative reweighted least squares algorithm to inverse a real time draft depth of the depth sounder; and finally superimposes the inverted draft depth and the sounding surface to output a new version water depth surface. The application changes the traditional periodic offline water depth survey into real time online updating along with the ship, effectively overcomes the water depth data lag problem caused by dynamic water level change and terrain siltation, and significantly improves the data timeliness.

Description

Technical Field

[0001] This invention relates to the technical field of inland waterway depth updating methods, specifically to a method for updating waterway depth. Background Technology

[0002] The updating of waterway depth data mainly relies on periodic manual surveys by waterway management departments, which are then processed to form the water depth data layer on electronic waterway charts. However, the update cycle of electronic waterway charts usually exceeds three months. For example, inland waterways are prone to dynamic fluctuations in water level due to rainy and dry seasons, seasonal siltation, and rapid topographic changes caused by shoreline erosion, resulting in significant deviations between the water depths marked on electronic waterway charts and the actual navigation environment.

[0003] Especially in complex scenarios such as narrow inland waterways and shallow water areas, traditional static draft monitoring methods are insufficient to calibrate the actual navigation conditions of the waterway in real time, leading to the risk of ships running aground or hitting the bottom. Therefore, there is an urgent need to develop a water depth data update mechanism based on the ship's self-sensing during navigation. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of this invention is to propose a method for updating the channel depth in order to solve the problems mentioned in the background section above.

[0005] This invention is achieved through the following technical solution: A method for updating channel depth, the method comprising the following steps: S1. Elevation sounder is mounted on the ship to acquire discrete new sounding point data, wherein the new sounding point includes: new depth, timestamp, and coordinates of the detection point; S2. Use the concave shell boundary extraction algorithm and the irregular triangular mesh interpolation algorithm to generate a sounding surface for the new sounding point; S3. Obtain the old version of the water depth surface recorded in the electronic navigation chart. Both the sounding surface and the old version of the water depth surface are extracted into point sets. Projection processing is performed using a unified coordinate reference system to obtain registration point pairs. S4. The registration point pair is used to invert the draft of the depth sounder using the Huber loss function and the iterative reweighted least squares algorithm. S5. The depth of the sounder obtained by inversion is superimposed on the sounding surface to obtain a new version of the water depth surface.

[0006] Furthermore, the depth sounder is installed on the bottom surface of the ship, and the draft of the depth sounder is equal to the draft of the ship.

[0007] Furthermore, step S2 includes the following sub-steps: S21. Apply the concave shell boundary extraction algorithm to the new sounding point to form a preliminary sounding coverage area; S22. Obtain the geometric boundary of the land area recorded in the electronic navigation chart, call the boundary difference algorithm of the GDAL library, perform spatial difference operation on the geometric boundary of the land area and the preliminary sounding coverage, remove the land area from the preliminary sounding coverage, and output the effective water depth area containing only the water area. S23. Convert the coordinates of the new sounding points within the effective water depth domain into a two-dimensional array format, and use the irregular triangular mesh interpolation algorithm to perform spatial interpolation on the discrete new sounding points within the effective water depth domain to generate the sounding surface covering the entire effective water depth domain.

[0008] Furthermore, step S2 also includes the following sub-steps: S24. Call the GDAL library vector mask grid clipping algorithm to clip the sounding surface using the effective water depth region as a mask, remove the remaining land area in the grid, and output a new sounding surface.

[0009] Furthermore, step S3 includes the following sub-steps: S31. Call the contour line extraction algorithm of GDAL library, scan the new sounding surface at preset intervals, extract the contour line set, and generate a new sounding line; The new depth sounding surface Consisting of several new depth gauges Composed of a collection; No. A new depth gauge line From several new depth sounding points Composed of a collection; Each new sounding point Includes the following parameters, ,in, Indicates new measuring point Spatial coordinates; Indicates new measuring point The water depth value; Indicates new measuring point timestamp; The old version of the water depth surface From several old versions of depth lines Composed of a collection; No. The old version of the depth line mentioned above From several water depth points Composed of a collection; Each water depth point Includes the following parameters, ,in, Indicates water depth spatial coordinates, Indicates water depth The electronic navigation channel icon water depth value, Indicates water depth timestamp; S32. Calculate the new depth gauge using the directed Hausdorff distance algorithm. To the old version of the depth line Directed distance: ; The old depth line was calculated using the directed Hausdorff distance algorithm. To the new depth gauge Directed distance: ; in, Indicates the directed Hausdorff distance; Indicates the new depth gauge To the old version of the depth line The two-dimensional Euclidean distance; Indicates the old version of the depth line To the new depth gauge The two-dimensional Euclidean distance; S33. Use the symmetric Hausdorff distance algorithm to define the depth measurement line for each new depth line. Match the most similar old version depth line Specifically, it is done through the following formula: ; S34. Using the line-to-line matching formula, for each new depth measurement line... traverse all Old version of the depth line Calculate the new depth gauge line With each old version of the depth line Choose the symmetric Hausdorff distance that minimizes the distance. The matching object is specifically determined by the following formula: ; S35. Using the nearest point search formula, for each new measuring point of a new depth measurement line... Traverse its corresponding old version depth line All water depths on This allows us to find the nearest water depth. Specifically, it is done through the following formula: ; S36. The new measurement point found in step S35 With water depth The matching process yields the registration point pairs, and the expression for each registration point pair is: .

[0010] Furthermore, step S4 includes the following sub-steps: S41. Calculate the residuals for all the registration point pairs, using the following formula: ; in: Indicates the record number on the electronic navigation chart. The water depth at the point; This indicates the first measurement taken by the depth sounder. The water depth at the point; Indicates the total number of registration point pairs; S42. Construct the time-exponentially decaying weight, the formula of which is as follows: ; in, Indicates the first Initial time weights for each registration point pair; This represents the time decay factor, which controls the rate at which historical data is affected. The timestamp indicates the current moment of the sounding operation; Indicates the first The timestamp of the acquisition of each registration point pair; S43. The draft of the depth sounder is estimated using the following formula: ; in, This represents the initial draft estimate of the depth sounder; S44. The draft of the depth sounder is calculated iteratively using the following formula: ; in, Indicates the first During the nth iteration The draft error of the depth sounder at each point; For the first The draft estimate of the depth sounder in the next iteration; S45. The Huber threshold is adaptively calculated using the following formula. : Calculate the median of the residuals : ; Calculate the median MAD, which is the absolute deviation of the residuals relative to the median: ; Calculate Huber threshold : ; S46. Based on the draft error of the current depth sounder With Huber threshold Relationship calculation During the nth iteration Huber weight at each point Its formula is: ; S47. Combining the initial time weight and Huber weight, update the... During the nth iteration The overall weight of each point Its formula is: ; S48. Using the updated comprehensive weights, recalculate the first... The formula for the draft estimate of the depth sounder in the next iteration is: ; Convergence criteria: If satisfied or number of iterations If the result is positive, then output the final draft estimate D; otherwise, return to step S44 to continue iterating. Indicates the maximum number of iterations. This represents the iteration convergence threshold.

[0011] Furthermore, step S41 is followed by the following sub-steps: S411, Regarding the residual set Sort the data and calculate the first quartile. and the third and fourth quartiles The interquartile range is obtained. ; S412. Remove outlier registration point pairs using the following formula: like or If the registration point pair is found to be abnormal, it will be removed. It is a constant.

[0012] Furthermore, in step S411, the first quartile 25th percentile, third and fourth percentiles It is at the 75th percentile.

[0013] On the other hand, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method described in any of the preceding claims.

[0014] The beneficial effects of this invention are as follows: By utilizing the data continuously collected by the depth sounder during ship navigation, this method transforms water depth updates from periodic offline surveys to an online process performed in real time on board the ship. This overcomes the problem of water depths marked on electronic navigation charts not matching the actual hydrological environment due to water level fluctuations during rainy and dry seasons and siltation. It significantly improves the timeliness of water depth data, greatly reduces the economic and time costs of updating waterway water depth data, and makes large-scale, high-frequency waterway maintenance possible, providing an efficient technical means for the construction of smart waterways and digital shipping. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for updating channel depth according to the present invention.

[0016] Figure 2 This is a schematic diagram showing the relationship between the draft of the depth sounder of this invention, the new depth measurement, and the old water depth. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be noted that the description of these embodiments is for the purpose of aiding understanding the present invention, but does not constitute a limitation thereof. Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0018] Reference Figure 1 As shown, a method for updating channel depth includes the following steps: S1. Elevation sounder is mounted on the ship to acquire discrete new sounding point data, wherein the new sounding point includes: new depth, timestamp, and coordinates of the detection point; S2. Use the concave shell boundary extraction algorithm and the irregular triangular mesh interpolation algorithm to generate a sounding surface for the new sounding point; S3. Obtain the old version of the water depth surface recorded in the electronic navigation chart. Both the sounding surface and the old version of the water depth surface are extracted into point sets. Projection processing is performed using a unified coordinate reference system to obtain registration point pairs. S4. The registration point pair is used to invert the draft of the depth sounder using the Huber loss function and the iterative reweighted least squares algorithm. S5. The depth of the sounder obtained by inversion is superimposed on the sounding surface to obtain a new version of the water depth surface.

[0019] During navigation, ships continuously collect new sounding point data using depth sounders. This invention utilizes a "continuous monitoring driven by historical sounding data" mechanism. During daily navigation, the discrete water depth information continuously generated by the depth sounder automatically accumulates new sounding points at different times and locations, and then regenerates them into sounding surfaces. The old water depth surface and the sounding surface are converted into point sets, and each point is matched on the coordinates to obtain registration point pairs. The draft of the depth sounder is deduced from the registration point pairs. The sum of the draft of the depth sounder and the height of the new sounding point equals the new water depth height. The updated water depth contour lines are reconstructed using these points to form a new channel water depth data file, realizing the dynamic updating of water depth data on electronic navigation charts.

[0020] Without having to wait for the waterway department's offline survey every three months, the ship can obtain water depth data that is consistent with the actual terrain in real time. This completely solves the problems of long measurement cycles and delayed updates in traditional methods, and achieves continuous spatiotemporal coverage and real-time updates of waterway depth, significantly improving the timeliness of water depth data and the ability to ensure navigation safety.

[0021] Reference Figure 2 As shown in the preferred embodiment, the depth sounder is installed on the bottom of the ship, and the draft of the depth sounder is equal to the draft of the ship. Therefore, there is no need to install an additional draft sensor or perform cumbersome draft calibration; the ship's actual draft can be directly derived from the measured water depth of the depth sounder. This simplifies the system structure, reduces hardware costs, and eliminates draft conversion errors caused by differences in installation location, improving the real-time performance and accuracy of ship draft estimation.

[0022] Step S2 includes the following sub-steps: S21. Apply the concave shell boundary extraction algorithm to the new sounding point to form a preliminary sounding coverage area; S22. Obtain the geometric boundary of the land area recorded in the electronic navigation chart, call the boundary difference algorithm of the GDAL library, perform spatial difference operation on the geometric boundary of the land area and the preliminary sounding coverage, remove the land area from the preliminary sounding coverage, and output the effective water depth area containing only the water area. S23. Convert the coordinates of the new sounding points within the effective water depth domain into a two-dimensional array format, and use the irregular triangular mesh interpolation algorithm to perform spatial interpolation on the discrete new sounding points within the effective water depth domain to generate the sounding surface covering the entire effective water depth domain.

[0023] In the above embodiment, a concave hull boundary extraction algorithm is used, and the boundary compactness is controlled by adjusting the maximum side length threshold of the triangulation network to generate a preliminary sounding coverage area. Then, the GDAL library boundary difference algorithm is called to remove land geometry objects from the preliminary sounding coverage area, generating an effective water depth region containing only water areas.

[0024] Compared to the boundary generated by the convex hull algorithm, which contains a large number of invalid regions, leading to increased interpolation calculations and reduced accuracy, the present invention uses a concave hull boundary extraction algorithm that can better fit the actual water morphology. Compared to the convex hull algorithm, it reduces the invalid coverage area by about 30-50%, providing a more accurate basic geometric framework for subsequent land area removal and reducing invalid interpolation calculations in step S24.

[0025] In step S23, spatial interpolation is performed on discrete new sounding points within the effective water depth domain using an irregular triangular mesh interpolation algorithm to generate a sounding surface with a high-resolution water depth grid.

[0026] The sounding surface generated in step S23 may retain a small number of land area pixels at the boundary, affecting the quality of the final result. To solve the above problem, in this invention, step S2 further includes the following sub-steps: S24. Call the GDAL library vector mask grid clipping algorithm to clip the sounding surface using the effective water depth region as a mask, remove the remaining land area in the grid, and output a new sounding surface.

[0027] The gdalwarp function or Clip tool from the GDAL library is called to precisely crop the sounding raster data, using the effective depth domain vector boundary obtained in step S22 as a mask. This thoroughly removes any remaining land areas from the raster data, ensuring that the final depth model is strictly limited to the water area, thus improving the production standardization and practicality of the new sounding.

[0028] Furthermore, step S3 includes the following sub-steps: S31. Call the contour line extraction algorithm of GDAL library, scan the new sounding surface at preset intervals, extract the contour line set, and generate a new sounding line; The new depth sounding surface Consisting of several new depth gauges Composed of a collection; No. A new depth gauge line From several new depth sounding points Composed of a collection; Each new sounding point Includes the following parameters, ,in, Indicates new measuring point Spatial coordinates; Indicates new measuring point The water depth value; Indicates new measuring point timestamp; The old version of the water depth surface From several old versions of depth lines Composed of a collection; No. The old version of the depth line mentioned above From several water depth points Composed of a collection; Each water depth point Includes the following parameters, ,in, Indicates water depth spatial coordinates, Indicates water depth The electronic navigation channel icon water depth value, Indicates water depth timestamp; S32. Calculate the new depth gauge using the directed Hausdorff distance algorithm. To the old version of the depth line Directed distance: ; The old depth line was calculated using the directed Hausdorff distance algorithm. To the new depth gauge Directed distance: ; in, Indicates the directed Hausdorff distance; Indicates the new depth gauge To the old version of the depth line The two-dimensional Euclidean distance; Indicates the old version of the depth line To the new depth gauge The two-dimensional Euclidean distance; S33. Use the symmetric Hausdorff distance algorithm to define the depth measurement line for each new depth line. Match the most similar old version depth line Specifically, it is done through the following formula: ; S34. Using the line-to-line matching formula, for each new depth measurement line... traverse all Old version of the depth line Calculate the new depth gauge line With each old version of the depth line Choose the symmetric Hausdorff distance that minimizes the distance. The matching object is specifically determined by the following formula: ; S35. Using the nearest point search formula, for each new measuring point of a new depth measurement line... Traverse its corresponding old version depth line All water depths on This allows us to find the nearest water depth. Specifically, it is done through the following formula: ; S36. The new measurement point found in step S35 With water depth The matching process yields the registration point pairs, and the expression for each registration point pair is: .

[0029] In step S31, since the sounding surface generated in step S2 and the old version of the electronic navigation chart cannot be directly matched point-to-point, they need to be converted into discrete point sets to eliminate data format differences and provide support for subsequent registration.

[0030] The contour line extraction algorithm of the GDAL library is called to scan the new sounding surface and the old water depth surface at preset intervals (such as 0.5 meters) to extract a set of contour lines. Each contour line consists of a series of ordered points, and each point contains coordinates, water depth and timestamp attributes.

[0031] Since the new depth gauge line and the old depth gauge line may deviate in shape and position due to terrain changes or measurement errors, it is necessary to quantify their spatial differences to assess similarity. Therefore, in step S32, the present invention adopts the directed Hausdorff distance algorithm. The directed distance can capture the local feature differences of linear geometry. Furthermore, the present invention avoids single-direction deviation through bidirectional calculation, providing multi-dimensional quantitative basis for similarity matching.

[0032] Furthermore, a symmetric Hausdorff distance algorithm is used to comprehensively measure the overall similarity between the new depth sounding line and the old depth sounding line, avoiding the one-sidedness of the directed Hausdorff distance algorithm in step S32. The symmetric Hausdorff distance algorithm can eliminate direction bias and more robustly reflect the spatial fit between lines, making it particularly suitable for winding river channels or complex terrain scenarios.

[0033] Step S34 is used for each new depth gauge line. Quickly extract from a large number of old depth lines The most similar objects are selected from the samples, and new depth gauges are calculated. With each old version of the depth line The symmetrical Hausdorff distance is used to select the old depthline with the smallest distance. As the matching object.

[0034] After online line matching is completed, the newly matched depth measurement line is matched in step S35. Each new measuring point Traverse its corresponding old version depth line All water depths on The Euclidean distance is calculated and the nearest point is found, thereby achieving point-level spatial alignment, eliminating registration errors caused by differences in the shape of contour lines, and providing a high-precision data foundation for draft inversion.

[0035] In step S36, each new measurement point obtained in step S35 is... With the nearest water depth Pairing is performed to form a set of registration point pairs. These registration point pairs are used to directly link the old and new water depth data, ensuring the spatiotemporal consistency of the data during draft inversion and simplifying the subsequent calculation process.

[0036] This invention introduces curve-level matching through the Hausdorff distance algorithm. By measuring the global worst-case deviation using directed and symmetric Hausdorff distance, it ensures optimal overall shape alignment, effectively solving spatial deviation problems caused by ship positioning errors, electronic chart lag, and environmental changes. For example, inland waterways experience seasonal changes in channel morphology due to siltation or erosion, resulting in significant differences between the old and new versions of depth gauges. By utilizing the overall shape matching characteristics of Hausdorff distance, even if the channel outline changes, accurate registration between the new and old depth gauges can still be achieved based on overall morphological similarity.

[0037] Furthermore, step S4 includes the following sub-steps: S41. Calculate the residuals for all the registration point pairs, using the following formula: ; in: Indicates the record number on the electronic navigation chart. The water depth at the point; This indicates the first measurement taken by the depth sounder. The water depth at the point; Indicates the total number of registration point pairs; S42. Construct the time-exponentially decaying weight, the formula of which is as follows: ; in, Indicates the first Initial time weights for each registration point pair; This represents the time decay factor, which controls the rate at which historical data is affected. The timestamp indicates the current moment of the sounding operation; Indicates the first The timestamp of the acquisition of each registration point pair; S43. The draft of the depth sounder is estimated using the following formula: ; in, This represents the initial draft estimate of the depth sounder; S44. The draft of the depth sounder is calculated iteratively using the following formula: ; in, Indicates the first During the nth iteration The draft error of the depth sounder at each point; For the first The draft estimate of the depth sounder in the next iteration; S45. The Huber threshold is adaptively calculated using the following formula. : Calculate the median of the residuals : ; Calculate the median MAD, which is the absolute deviation of the residuals relative to the median: ; Calculate Huber threshold : ; S46. Based on the draft error of the current depth sounder With Huber threshold Relationship calculation During the nth iteration Huber weight at each point Its formula is: ; S47. Combining the initial time weight and Huber weight, update the... During the nth iteration The overall weight of each point Its formula is: ; S48. Using the updated comprehensive weights, recalculate the first... The formula for the draft estimate of the depth sounder in the next iteration is: ; Convergence criteria: If satisfied or number of iterations If the result is positive, then output the final draft estimate D; otherwise, return to step S44 to continue iterating. Indicates the maximum number of iterations. This represents the iteration convergence threshold.

[0038] In the above embodiment, step S42 assigns a time decay weight to each registration point pair; the closer the registration point pair is to the current one, the greater its time weight. The larger the draft, the better. To avoid significant interference from early data in current draft estimates, ensure that recent measurements contribute the most to draft estimates, respond quickly to dynamic changes in water level, and appropriately retain historical data trends to avoid draft estimation bias caused by short-term fluctuations.

[0039] In step S44, the draft error is iteratively calculated using the iterative reweighted least squares algorithm. The error result is then passed to step S46 to calculate the new Huber weights. By combining the Huber loss function with the iterative reweighted least squares algorithm for robust estimation, the final draft estimate D is output, which helps to improve the noise resistance and accuracy of draft estimation and enhances robustness.

[0040] Using the median in step S45 Calculate the adaptive Huber threshold using the median absolute deviation (MAD). This avoids the difficulty of relying on empirically preset thresholds, enhancing the algorithm's adaptability and practicality. The threshold is adaptively calculated based on the current residual distribution, achieving an optimal balance between handling normal data (using quadratic loss for statistical efficiency) and outlier data (using linear loss for robustness), with a time decay factor. To control the rate at which historical data impacts data, it is typically set to 0.1-0.5 based on the data update frequency.

[0041] By step S46, the draft error is assessed. With Huber threshold The magnitude relationship, for the normal error point, i.e. Assign high weights to achieve precision; address abnormal error points, i.e. By assigning low weights, interference is reduced, and "abnormal noise" in the measured data (such as instantaneous mismeasurement caused by water flow impact on the depth sounder, and mismatch of registration point pairs) is effectively resisted.

[0042] By combining the time-exponential decay weight Huber weight in step S47, the first... The combined weight of the next iteration This approach ensures that during the registration point pairing process, both the "time freshness" of the data (prioritizing recent data) and the "error reliability" of the data (prioritizing normal error data) are considered, further optimizing the input data quality for draft estimation and improving the robustness of the output results.

[0043] Step S48, the convergence judgment mechanism avoids insufficient accuracy due to insufficient iteration or waste of computing resources due to excessive iteration, thus controlling computing costs while ensuring accurate results.

[0044] Furthermore, step S41 is followed by the following sub-steps: S411, Regarding the residual set Sort the data and calculate the first quartile. and the third and fourth quartiles The interquartile range is obtained. ; S412. Remove outlier registration point pairs using the following formula: like or If the registration point pair is found to be abnormal, it will be removed. It is a constant.

[0045] Furthermore, in step S411, the first quartile 25th percentile, third and fourth percentiles The 75th percentile is used to define the distribution range of normal residuals. Factor Generally, 1.5 is used.

[0046] Steps S411 and S412 effectively identify and remove outlier registration point pairs, reducing the interference of "extreme residuals" on draft estimation. For example, retaining outliers with extremely large residuals can cause the time decay weight calculation in S42 to be biased towards invalid data, thus causing the initial draft estimate in S43 to deviate from the true value. Subsequent iterative optimization will also struggle to converge to accurate results due to "starting point bias." This step, by purifying the set of registration point pairs, ensures that subsequent draft inversion is based on "high-quality, low-noise" data, directly improving the accuracy of the final draft estimate.

[0047] In step 5, the depth sounder draft value D obtained by inversion in steps S41 to S48 is superimposed on the depth sounding surface. Using methods such as steps S21 to S23, the isobaths are reconstructed through spatial interpolation and contour line fitting to obtain a new version of the water depth surface, thereby updating the electronic navigation chart.

[0048] On the other hand, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method described in any of the preceding claims.

[0049] In embodiments of the invention, a "readable storage medium" refers to any medium that participates in providing a program or instructions to a processor for execution. The medium can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical discs or magnetic disks, such as storage devices. Volatile media include dynamic memory, such as main memory. Transmission media include coaxial cables, copper wires, and optical fibers, including conductors containing buses. Transmission media can also take the form of acoustic or optical waves, such as acoustic or optical waves generated during radio frequency (RF) and infrared (IR) data communications. Common forms of readable storage media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs, any other optical media, punched cards, paper tape, any other physical media with a perforated pattern, RAM, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cartridges, carrier waves, or any other medium from which a computer can read. A program or instructions are stored on this readable storage medium, which, when executed by a processor, performs the registration method described above.

[0050] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0051] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" and "second" may explicitly or implicitly include one or more of that feature.

[0052] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the invention should be included within the scope of protection of the invention.

Claims

1. A method for updating channel depth, characterized in that, The method includes the following steps: S1. Elevation sounder is mounted on the ship to acquire discrete new sounding point data, wherein the new sounding point includes: new depth, timestamp, and coordinates of the detection point; S2. Use the concave shell boundary extraction algorithm and the irregular triangular mesh interpolation algorithm to generate a sounding surface for the new sounding point; S3. Obtain the old version of the water depth surface recorded in the electronic navigation chart. Both the sounding surface and the old version of the water depth surface are extracted into point sets. Projection processing is performed using a unified coordinate reference system to obtain registration point pairs. S4. The registration point pair is used to invert the draft of the depth sounder using the Huber loss function and the iterative reweighted least squares algorithm. S5. The depth of the sounder obtained by inversion is superimposed on the sounding surface to obtain a new version of the water depth surface.

2. The method for updating channel depth according to claim 1, characterized in that, The depth sounder is installed on the bottom of the ship, and the draft of the depth sounder is equal to the draft of the ship.

3. The method for updating channel depth according to claim 1, characterized in that, Step S2 includes the following sub-steps: S21. Apply the concave shell boundary extraction algorithm to the new sounding point to form a preliminary sounding coverage area; S22. Obtain the geometric boundary of the land area recorded in the electronic navigation chart, call the boundary difference algorithm of the GDAL library, perform spatial difference operation on the geometric boundary of the land area and the preliminary sounding coverage, remove the land area from the preliminary sounding coverage, and output the effective water depth area containing only the water area. S23. Convert the coordinates of the new sounding points within the effective water depth domain into a two-dimensional array format, and use the irregular triangular mesh interpolation algorithm to perform spatial interpolation on the discrete new sounding points within the effective water depth domain to generate the sounding surface covering the entire effective water depth domain.

4. The method for updating channel depth according to claim 3, characterized in that, Step S2 further includes the following sub-steps: S24. Call the GDAL library vector mask grid clipping algorithm to clip the sounding surface using the effective water depth region as a mask, remove the remaining land area in the grid, and output a new sounding surface.

5. The method for updating channel depth according to claim 4, characterized in that, Step S3 includes the following sub-steps: S31. Call the contour line extraction algorithm of GDAL library, scan the new sounding surface at preset intervals, extract the contour line set, and generate a new sounding line; The new depth sounding surface Consisting of several new depth gauges Composed of a collection; No. A new depth gauge line From several new depth sounding points Composed of a collection; Each new sounding point Includes the following parameters, ,in, Indicates new measuring point Spatial coordinates; Indicates new measuring point The water depth value; Indicates new measuring point timestamp; The old version of the water depth surface From several old versions of depth lines Composed of a collection; No. The old version of the depth line mentioned above From several water depth points Composed of a collection; Each water depth point Includes the following parameters, ,in, Indicates water depth spatial coordinates, Indicates water depth The electronic navigation channel icon water depth value, Indicates water depth timestamp; S32. Calculate the new depth gauge using the directed Hausdorff distance algorithm. To the old version of the depth line Directed distance: ； The old depth line was calculated using the directed Hausdorff distance algorithm. To the new depth gauge Directed distance: ; in, Indicates the directed Hausdorff distance; Indicates the new depth gauge To the old version of the depth line The two-dimensional Euclidean distance; Indicates the old version of the depth line To the new depth gauge The two-dimensional Euclidean distance; S33. Use the symmetric Hausdorff distance algorithm to define the depth measurement line for each new depth line. Match the most similar old version depth line Specifically, it is done through the following formula: ； S34. Using the line-to-line matching formula, for each new depth measurement line... traverse all Old version of the depth line Calculate the new depth gauge line With each old version of the depth line Choose the symmetric Hausdorff distance that minimizes the distance. The matching object is specifically determined by the following formula: ； S35. Using the nearest point search formula, for each new measuring point of a new depth measurement line... Traverse its corresponding old version depth line All water depths on This allows us to find the nearest water depth. Specifically, it is done through the following formula: ； S36. The new measurement point found in step S35 With water depth The matching process yields the registration point pairs, and the expression for each registration point pair is: 。 6. The method for updating channel depth according to claim 5, characterized in that, Step S4 includes the following sub-steps: S41. Calculate the residuals for all the registration point pairs, using the following formula: ； in: Indicates the record number on the electronic navigation chart. The water depth at the point; This indicates the first measurement taken by the depth sounder. The water depth at the point; Indicates the total number of registration point pairs; S42. Construct the time-exponentially decaying weight, the formula of which is as follows: ； in, Indicates the first Initial time weights for each registration point pair; This represents the time decay factor, which controls the rate at which historical data is affected. The timestamp indicates the current moment of the sounding operation; Indicates the first The timestamp of the acquisition of each registration point pair; S43. The draft of the depth sounder is estimated using the following formula: ； in, This represents the initial draft estimate of the depth sounder; S44. The draft of the depth sounder is calculated iteratively using the following formula: ； in, Indicates the first During the nth iteration The draft error of the depth sounder at each point; For the first The draft estimate of the depth sounder in the next iteration; S45. The Huber threshold is adaptively calculated using the following formula. : Calculate the median of the residuals : ； Calculate the median MAD, which is the absolute deviation of the residuals relative to the median: ； Calculate Huber threshold : ； S46. Based on the draft error of the current depth sounder With Huber threshold Relationship calculation During the nth iteration Huber weight at each point Its formula is: ； S47. Combining the initial time weight and Huber weight, update the... During the nth iteration The overall weight of each point Its formula is: ； S48. Using the updated comprehensive weights, recalculate the first... The formula for the draft estimate of the depth sounder in the next iteration is: ； Convergence criteria: If satisfied or number of iterations If the result is positive, then output the final draft estimate D; otherwise, return to step S44 to continue iterating. Indicates the maximum number of iterations. This represents the iteration convergence threshold.

7. A method for updating channel depth according to claim 6, characterized in that, The following sub-steps are included after step S41: S411, Regarding the residual set Sort the data and calculate the first quartile. and the third and fourth quartiles The interquartile range is obtained. ; S412. Remove outlier registration point pairs using the following formula: like or If the registration point pair is found to be abnormal, it will be removed. It is a constant.

8. A method for updating channel depth according to claim 7, characterized in that: In step S411, the first quartile 25th percentile, third and fourth percentiles It is at the 75th percentile.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, are used to implement the method as described in any one of claims 1 to 8.

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