Self-adaptive multi-beam survey line layout method based on Kriging interpolation prediction

Abstract

The invention discloses a Kriging interpolation prediction-based adaptive multi-beam survey line layout method, which belongs to the technical field of underwater surveying and mapping, is used for multi-beam survey line layout, and comprises the following steps of: predicting and laying survey lines based on a strip coverage rate by using an extreme value weighted water depth model; the weighted weight of an extreme value is adaptively adjusted according to the sudden change condition of the water depth of a measured water area, a Kriging interpolation model is used for carrying out water depth space interpolation prediction on a water area with an unmeasured water depth based on the water area with the measured water depth, and a variation function model is switched according to the terrain difference of the water area to optimize an interpolation prediction result. And based on the strip coverage rate and the water depth space predicted by interpolation, planning the spatial position of the next survey line, determining two end points of the new survey line according to the boundary of the water area to be deepened, and planning a complete survey line. According to the method, local water depth change characteristics can be effectively captured, a reliable basis is provided for follow-up survey line strip width estimation and spacing control, and continuous multi-beam survey lines with high coverage rate are automatically generated.

Description

Technical Field

[0001] The invention discloses an adaptive multi-beam survey line layout method based on Kriging interpolation prediction, belonging to the technical field of underwater surveying and mapping. Background Art

[0002] In the fields of underwater topography, water conservancy projects, channel dredging, and environmental surveys, the acquisition of high-precision depth data is fundamental. With the widespread application of unmanned survey vessels and multi-beam bathymetry systems, the efficiency and accuracy of bathymetry have been significantly improved. However, when conducting bathymetry in unknown or complex waters, how to automatically plan survey lines to achieve high coverage, low redundancy, and high measurement efficiency remains a key technical challenge. Traditional survey line planning often adopts a regular layout strategy, relying on pre-known survey area boundaries and average water depths. It lacks the ability to adaptively adjust to actual terrain features, often resulting in insufficient strip coverage, excessive survey line overlap, and an inability to adapt to irregular water boundaries and complex bottom shapes. Summary of the Invention

[0003] The purpose of the present invention is to provide an adaptive multi-beam survey line layout method based on Kriging interpolation prediction to solve the problems in the prior art of insufficient strip coverage of multi-beam survey line layout, excessive survey line overlap, and inability to adapt to irregular water boundaries and complex bottom shapes.

[0004] An adaptive multi-beam survey line layout method based on Kriging interpolation prediction includes: S1. Extract the convex hull boundary of the water area according to the depth of the water area to be measured, and ensure that the laid survey line covers the entire depth of the water area to be measured; S2. Setting the multi-beam opening angle value and the desired stripe coverage; S3. Determine the direction of the main survey line; S4. Use the extreme value weighted water depth model to predict and arrange the survey lines based on the strip coverage rate, and adaptively adjust the extreme value weighting according to the sudden change of water depth in the measured water area; S5. Use the Kriging interpolation model to perform spatial interpolation prediction of water depth for unmeasured water areas based on measured water depths, and switch the variogram model according to the differences in water terrain to optimize the interpolation prediction results; S6. Based on the strip coverage and the interpolation-predicted water depth space, plan the spatial position of the next survey line and determine the two end points of the new survey line according to the boundary of the water area to be measured; S7. Plan a complete survey line, which includes the main survey line, Z-shaped connecting survey lines between adjacent main survey lines, and inspection survey lines.

[0005] S1 includes, S1.1, using a multi-beam carrying platform to perform obstacle avoidance and following in the water area to be measured, moving along the natural boundary of the water area to measure the depth, obtaining a set of boundary points of the water area to be measured, and forming the range of the water area to be measured; S1.2, perform two-dimensional projection on the boundary point set of the water area to be measured, extract the convex hull vertices based on the two-dimensional convex hull algorithm Quickhull, filter out the convex hull boundary of the boundary point set of the water area to be measured, and output the coordinates of the convex hull vertices arranged in counterclockwise order. for: ; Where, It is convex hull coordinates, is the number of convex hull coordinates; S1.3. Call the convex hull internal point determination function to determine whether the point in the point set is within the boundary of the water area to be measured: ; Where, is the boundary set of the water area to be measured, The points are removed from the survey line. are the coordinates of the point in the water area to be measured.

[0006] The multi-beam opening angle value is 120° and the expected strip coverage is 25%; Multi-beam swath width for: ; Where, is the water depth of the current survey line layout area, is the multi-beam opening angle.

[0007] S3 includes fitting an approximate quadrilateral to the survey area based on the convex hull shape of the water area boundary, selecting the long side direction of the fitted quadrilateral as the main survey line direction, the ship width distance corresponding to the long side deviating from the main survey line direction as the initial survey line position, and taking the intersection of the initial survey line and the water area boundary as the starting and ending points of the survey line.

[0008] The extreme value weighted water depth model includes the introduction of the definition of weighting coefficients : ; ; Where, is the weight factor for extreme outliers, is the weight factor for mild outliers, is the first quartile, is the third quartile, is the interquartile range, For the The water depth at a known point; Extreme value weighted water depth for: ; Where, is the total number of known points.

[0009] S5 includes constructing polygonal strips for known points, and the water depth point set composed of polygonal strips for: ; Where, For the The spatial coordinates of a known point, For the The water depth at a known point; Multi-span extension sampling prediction based on polygonal strips to calculate unknown points Predicted water depth : ; ; Where, For the The weight of each known point; The relationship between the Kriging interpolation variogram and covariance is: ; Where, is the Kriging interpolation variogram, is the maximum covariance, is the covariance function, is the spatial distance between two points, and the prediction variance is minimized when solving the weight , is the water depth at the unknown point; The solution weight is: ; Where, It is known points and The variance function value between known points, The predicted point and the The variance function value between known points, is the Lagrange multiplier, It is The weight of the known points.

[0010] S6 includes calculating the predicted water depth value of the unknown point, estimating the water depth of the adjacent area, and determining the spacing between the next survey line and the previous survey line based on the multi-beam strip width and strip coverage; After determining the spatial position of the next survey line, the next survey line is intercepted according to the convex hull boundary condition of the water area to be measured, and the part where the next survey line intersects with the water area is retained. The two intersection points of the intercepted next survey line on the convex hull boundary are set as the starting point and end point of the next survey line.

[0011] S7 includes generating the main survey line. If the midpoint of the main survey line exceeds the depth water range to be measured, only the effective portion of the main survey line within the depth water range to be measured is retained, and subsequent main survey line generation prediction is terminated.

[0012] A zigzag connection strategy is introduced in the main survey line generation process, and zigzag survey lines are dynamically added between adjacent main survey lines, so that the main survey lines are connected end to end to form a continuous path structure.

[0013] Record the main survey line and generate a check survey line based on the ratio of the total length of the main survey line.

[0014] Compared with the existing technology, the present invention has the following beneficial effects: the present invention can effectively capture the characteristics of local water depth changes, thereby providing a reliable basis for subsequent survey line strip width estimation and spacing control, and automatically generate high-coverage, continuous multi-beam survey lines; effectively suppress the interference of abnormal water depth on strip width calculation, and predict the water depth of unsurveyed areas in real time, overcoming the problems of low deployment accuracy and poor adaptability of traditional methods; combining adaptive strip coverage strategy with connection survey line planning, it enhances the path planning accuracy and operating efficiency of unmanned ships in unknown waters. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is the linear model prediction planning line map; Figure 2 It is the spherical model prediction planning line map; Figure 3 It is a spherical model strip coverage map; Figure 4 It is the exponential model prediction planning line map; Figure 5 is the exponential model strip overlay; Figure 6 It is the Gaussian model prediction planning line map. DETAILED DESCRIPTION

[0016] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0017] An adaptive multi-beam survey line layout method based on Kriging interpolation prediction includes: S1. Extract the convex hull boundary of the water area according to the depth of the water area to be measured, and ensure that the laid survey line covers the entire depth of the water area to be measured; S2. Setting the multi-beam opening angle value and the desired stripe coverage; S3. Determine the direction of the main survey line; S4. Use the extreme value weighted water depth model to predict and arrange the survey lines based on the strip coverage rate, and adaptively adjust the extreme value weighting according to the sudden change of water depth in the measured water area; S5. Use the Kriging interpolation model to perform spatial interpolation prediction of water depth for unmeasured water areas based on measured water depths, and switch the variogram model according to the differences in water terrain to optimize the interpolation prediction results; S6. Based on the strip coverage and the interpolation-predicted water depth space, plan the spatial position of the next survey line and determine the two end points of the new survey line according to the boundary of the water area to be measured; S7. Plan a complete survey line, which includes the main survey line, Z-shaped connecting survey lines between adjacent main survey lines, and inspection survey lines.

[0018] S1 includes, S1.1, using a multi-beam carrying platform to perform obstacle avoidance and following in the water area to be measured, moving along the natural boundary of the water area to measure the depth, obtaining a set of boundary points of the water area to be measured, and forming the range of the water area to be measured; S1.2, perform two-dimensional projection on the boundary point set of the water area to be measured, extract the convex hull vertices based on the two-dimensional convex hull algorithm Quickhull, filter out the convex hull boundary of the boundary point set of the water area to be measured, and output the coordinates of the convex hull vertices arranged in counterclockwise order. for: ; Where, It is convex hull coordinates, is the number of convex hull coordinates; S1.3. Call the convex hull internal point determination function to determine whether the point in the point set is within the boundary of the water area to be measured: ; Where, is the boundary set of the water area to be measured, The points are removed from the survey line. are the coordinates of the point in the water area to be measured.

[0019] The multi-beam opening angle value is 120° and the expected strip coverage is 25%; Multi-beam swath width for: ; Where, is the water depth of the current survey line layout area, is the multi-beam opening angle.

[0020] S3 includes fitting an approximate quadrilateral to the survey area based on the convex hull shape of the water area boundary, selecting the long side direction of the fitted quadrilateral as the main survey line direction, the ship width distance corresponding to the long side deviating from the main survey line direction as the initial survey line position, and taking the intersection of the initial survey line and the water area boundary as the starting and ending points of the survey line.

[0021] The extreme value weighted water depth model includes the introduction of the definition of weighting coefficients : ; ; Where, is the weight factor for extreme outliers, is the weight factor for mild outliers, is the first quartile, is the third quartile, is the interquartile range, For the The water depth at a known point; Extreme value weighted water depth for: ; Where, is the total number of known points.

[0022] S5 includes constructing polygonal strips for known points, and the water depth point set composed of polygonal strips for: ; Where, For the The spatial coordinates of a known point, For the The water depth at a known point; Multi-span extension sampling prediction based on polygonal strips to calculate unknown points Predicted water depth : ; ; Where, For the The weight of each known point; The relationship between the Kriging interpolation variogram and covariance is: ; Where, is the Kriging interpolation variogram, is the maximum covariance, is the covariance function, is the spatial distance between two points, and the prediction variance is minimized when solving the weight , is the water depth at the unknown point; The solution weight is: ; Where, It is known points and The variance function value between known points, The predicted point and the The variance function value between known points, is the Lagrange multiplier, It is The weight of the known points.

[0023] S6 includes calculating the predicted water depth value of the unknown point, estimating the water depth of the adjacent area, and determining the spacing between the next survey line and the previous survey line based on the multi-beam strip width and strip coverage; After determining the spatial position of the next survey line, the next survey line is intercepted according to the convex hull boundary condition of the water area to be measured, and the part where the next survey line intersects with the water area is retained. The two intersection points of the intercepted next survey line on the convex hull boundary are set as the starting point and end point of the next survey line.

[0024] S7 includes generating the main survey line. If the midpoint of the main survey line exceeds the depth water range to be measured, only the effective portion of the main survey line within the depth water range to be measured is retained, and subsequent main survey line generation prediction is terminated.

[0025] A zigzag connection strategy is introduced in the main survey line generation process, and zigzag survey lines are dynamically added between adjacent main survey lines, so that the main survey lines are connected end to end to form a continuous path structure.

[0026] Record the main survey line and generate a check survey line based on the ratio of the total length of the main survey line.

[0027] In the specific implementation of the present invention, a variety of Kriging interpolation variograms are used, including Linear linear model, Spherical spherical model, Exponential exponential model, Gaussian Gaussian model; in the weight calculation, The three values ​​of refer to Table 1.

[0028] Table 1 Three values ​​of ; The present invention uses a linear model to predict the planned survey line such as Figure 1 As shown, the spherical model predicts the planned survey line as follows Figure 2 As shown, the spherical model strip coverage diagram is as follows Figure 3 As shown, the exponential model predicts the planned survey line as follows Figure 4 As shown, the exponential model strip coverage diagram is as follows Figure 5 As shown, the Gaussian model predicts the planned survey line as follows Figure 6 As shown in Table 2, the Kriging interpolation variogram is selected and adjusted according to the actual underwater terrain characteristics of the survey area to achieve a more reasonable fitting and prediction of the water depth distribution under different terrain conditions.

[0029] Table 2. Selection of Kriging interpolation variogram .

[0030] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents, and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive multi-beam survey line layout method based on Kriging interpolation prediction, characterized in that: include: S1. Extract the convex hull boundary of the water area according to the depth of the water area to be measured, and ensure that the laid survey line covers the entire depth of the water area to be measured; S2. Setting the multi-beam opening angle value and the desired stripe coverage; S3. Determine the direction of the main survey line; S4. Use the extreme value weighted water depth model to predict and arrange the survey lines based on the strip coverage rate, and adaptively adjust the extreme value weighting according to the sudden change of water depth in the measured water area; S5. Use the Kriging interpolation model to perform spatial interpolation prediction of water depth for unmeasured water areas based on measured water depths, and switch the variogram model according to the differences in water terrain to optimize the interpolation prediction results; S6. Based on the strip coverage and the interpolation-predicted water depth space, plan the spatial position of the next survey line and determine the two end points of the new survey line according to the boundary of the water area to be measured; S7. Plan a complete survey line, which includes the main survey line, Z-shaped connecting survey lines between adjacent main survey lines, and inspection survey lines.

2. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 1 is characterized in that: S1 includes, S1.1, using a multi-beam carrying platform to perform obstacle avoidance and following in the water area to be measured, moving along the natural boundary of the water area to measure the depth, obtaining a set of boundary points of the water area to be measured, and forming the range of the water area to be measured; S1.2, perform two-dimensional projection on the boundary point set of the water area to be measured, extract the convex hull vertices based on the two-dimensional convex hull algorithm Quickhull, filter out the convex hull boundary of the boundary point set of the water area to be measured, and output the coordinates of the convex hull vertices arranged in counterclockwise order. for: ； Where, It is convex hull coordinates, is the number of convex hull coordinates; S1.

3. Call the convex hull internal point determination function to determine whether the point in the point set is within the boundary of the water area to be measured: ； Where, is the boundary set of the water area to be measured, The points are removed from the survey line. are the coordinates of the point in the water area to be measured.

3. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 2 is characterized in that: The multi-beam opening angle value is 120° and the expected strip coverage is 25%; Multi-beam swath width for: ； Where, is the water depth of the current survey line layout area, is the multi-beam opening angle.

4. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 3 is characterized in that: S3 includes fitting an approximate quadrilateral to the survey area based on the convex hull shape of the water area boundary, selecting the long side direction of the fitted quadrilateral as the main survey line direction, the ship width distance corresponding to the long side deviating from the main survey line direction as the initial survey line position, and taking the intersection of the initial survey line and the water area boundary as the starting and ending points of the survey line.

5. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 4 is characterized in that: The extreme value weighted water depth model includes the introduction of the definition of weighting coefficients : ； ； Where, is the weight factor for extreme outliers, is the weight factor for mild outliers, is the first quartile, is the third quartile, is the interquartile range, For the The water depth at a known point; Extreme value weighted water depth for: ； Where, is the total number of known points.

6. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 5, characterized in that: S5 includes constructing polygonal strips for known points, and the water depth point set composed of polygonal strips for: ； Where, For the The spatial coordinates of a known point, For the The water depth at a known point; Multi-span extension sampling prediction based on polygonal strips to calculate unknown points Predicted water depth : ； ； Where, For the The weight of each known point; The relationship between the Kriging interpolation variogram and covariance is: ； Where, is the Kriging interpolation variogram, is the maximum covariance, is the covariance function, is the spatial distance between two points, and the prediction variance is minimized when solving the weight , is the water depth at the unknown point; The solution weight is: ； Where, It is known points and The variance function value between known points, The predicted point and the The variance function value between known points, is the Lagrange multiplier, It is The weight of the known points.

7. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 6, characterized in that: S6 includes calculating the predicted water depth value of the unknown point, estimating the water depth of the adjacent area, and determining the spacing between the next survey line and the previous survey line based on the multi-beam strip width and strip coverage; After determining the spatial position of the next survey line, the next survey line is intercepted according to the convex hull boundary condition of the water area to be measured, and the part where the next survey line intersects with the water area is retained. The two intersection points of the intercepted next survey line on the convex hull boundary are set as the starting point and end point of the next survey line.

8. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 7, characterized in that: S7 includes generating the main survey line. If the midpoint of the main survey line exceeds the depth water range to be measured, only the effective portion of the main survey line within the depth water range to be measured is retained, and subsequent main survey line generation prediction is terminated.

9. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 8, characterized in that: A zigzag connection strategy is introduced in the main survey line generation process, and zigzag survey lines are dynamically added between adjacent main survey lines, so that the main survey lines are connected end to end to form a continuous path structure.

10. The adaptive multi-beam survey line layout method based on Kriging interpolation prediction according to claim 9, characterized in that: Record the main survey line and generate a check survey line based on the ratio of the total length of the main survey line.

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