Multi-beam sounding error processing method for jointly detecting gross error and compensating system deviation

Abstract

The invention discloses a multi-beam sounding error processing method for jointly detecting gross error and compensating system deviation, belongs to the technical field of multi-beam sounding data processing, and solves the problem that a multi-beam sounding result at the present stage is comprehensively influenced by sound velocity profile measurement error and representative error thereof, installation deflection angle observation error, attitude error and the like. The method comprises the following steps: constructing a submarine topography multi-beam sounding observation curved surface, constructing a submarine topography multi-beam sounding correction curved surface, calculating to obtain a multi-beam sounding systematic deviation correction number, and obtaining a submarine topography multi-beam sounding result curved surface after gross error elimination and system deviation compensation. The method effectively solves the problem of combined processing of gross errors and system deviations in multi-beam sounding data, can significantly improve the data quality, improves the strip splicing effect, and especially has outstanding advantages for compensating systematic deviations of deepwater areas or edge beams.

Description

Technical Field

[0001] This invention belongs to the field of multibeam bathymetry data processing technology, specifically involving a multibeam bathymetry error processing method that combines gross error detection and system deviation compensation. Background Technology

[0002] Multibeam bathymetry, as a core tool for marine surveying and underwater topographic exploration, is widely used in seabed topographic surveying, channel dredging, submarine pipeline laying, and marine resource exploration. However, the quality of multibeam bathymetry data is complexly affected by various error sources. In addition to inherent instrument errors, external uncertainties such as time-varying parameters of the dynamic environment (e.g., changes in sound velocity profiles) and carrier motion and attitude parameters (e.g., roll and pitch deviations) introduce significant interference, resulting in the simultaneous presence of gross errors (outliers), systematic biases, and random errors in the bathymetry data. Currently, various methods have been proposed for processing multibeam bathymetry errors, but most studies follow the "separate processing" approach, that is, processing gross errors and systematic biases independently. However, in addition to being affected by inherent instrument errors, multibeam bathymetry data is also affected by various uncertainties and external error sources closely related to time-varying parameters of the dynamic environment and carrier motion and attitude parameters. This results in bathymetry data containing not only a small amount of outlier data but also systematic biases with colored noise characteristics. Although environmental corrections are applied to the raw multibeam bathymetry data according to the relevant technical requirements of the operating procedures during the post-processing stage, the results are still affected by a combination of uncontrollable residual errors, including sound velocity profile measurement errors and their representative errors, installation angle observation errors, and attitude errors. These effects are generally systematic and difficult to separate and compensate for using traditional correction methods. In deep water areas, the combined impact of these residual errors on the edge beams is particularly significant, substantially affecting the quality of multibeam bathymetry results. Since gross errors in bathymetry data have a coupling effect on system bias correction, we propose a multibeam bathymetry error processing method that jointly detects gross errors and compensates for system biases to address the above issues. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies by providing a multibeam echo sounding error processing method that combines gross error detection and system deviation compensation. This method solves the problem that current multibeam echo sounding results are affected by a combination of uncontrollable residual errors, including sound velocity profile measurement errors and their representative errors, installation angle observation errors, and attitude errors.

[0004] This invention is implemented as follows: a multibeam bathymetry error processing method that jointly detects gross errors and compensates for system biases, comprising:

[0005] S10: Obtain the basic sounding data, select iterative robust filtering based on the trend surface, construct the seabed topography multibeam sounding observation surface based on the basic sounding data, perform gross error detection and removal on the basic sounding data through the seabed topography multibeam sounding observation surface, and output the basic sounding data after gross error removal.

[0006] S20, Load the bathymetry baseline data after gross error removal, and construct the seabed topography multibeam bathymetry correction surface based on the bathymetry baseline data after gross error removal;

[0007] S30, load the constructed seabed topography multibeam bathymetry observation surface and seabed topography multibeam bathymetry correction surface, calculate the surface difference between the seabed topography multibeam bathymetry observation surface and the seabed topography multibeam bathymetry correction surface, and obtain the multibeam bathymetry systematic deviation correction number;

[0008] S40, subtract the multibeam bathymetry systematic deviation correction from the bathymetry basic data after gross error removal, to obtain the seabed topography multibeam bathymetry result surface after gross error removal and systematic deviation compensation.

[0009] Preferably, the method for constructing a multibeam bathymetry observation surface for seabed topography based on bathymetry data includes:

[0010] Obtain seafloor topographic data for the survey area block. Based on this data, model the seafloor topography depth as a combination of a general polynomial and a trigonometric polynomial. The combination of the general polynomial and the trigonometric polynomial is expressed as:

[0011] (1)

[0012] In the formula, The depth of the seabed topography; The latitude and longitude coordinates of the measurement points are used (with the lower left corner of the measurement area as the origin, and uniformly converted to angle minutes). , and The measurement blocks are located at the latitude line. and meridian Coverage range in the direction; where:

[0013]

[0014]

[0015] , , , and For the coefficients to be determined, based on the seabed topographic data and bathymetry data of the survey area, select the highest order and combination of the general polynomial and trigonometric polynomial in formula (1), and let For the first The multibeam bathymetry observations at each measurement point have an observation error correction factor of [value missing]. Then we have:

[0016] (2)

[0017] Substitute formula (1) into formula (2), based on the measurement area... The following set of error equations is derived from the multibeam bathymetry observations:

[0018] (3)

[0019] In the formula, This is the correction vector for water depth observation errors; The coefficient matrix is ​​determined based on the coordinates of the measuring points and formula (1); For the reason undetermined coefficients , , , and The unknown vector formed; This is a vector of water depth observations;

[0020] Based on the principle of unequal precision least squares approximation, the most probable solution for the undetermined coefficients is obtained, where the most probable solution for the undetermined coefficients in formula (3) is:

[0021] (4)

[0022] In formula (4), The weight matrix of the multibeam bathymetry observations;

[0023] Based on formula (4), the iterative solution of the unknown vector based on the equivalent weight robust estimation method is obtained as follows:

[0024] (5)

[0025] (6)

[0026] In the formula, To the initial weight matrix of the multibeam bathymetry observations and the first The equivalent weight matrix related to the residuals of the next iteration observations, and the size of its equivalent weight factor is determined by the IGGⅢ scheme;

[0027] Equivalent weighting factors are calculated based on the IGGIII scheme, and gross errors are identified and eliminated based on these equivalent weighting factors.

[0028] Preferably, when calculating the equivalent weight factor according to the IGGIII scheme, the formula for calculating the equivalent weight factor is expressed as follows:

[0029] (7)

[0030] In the formula, Initial weighting factors for multibeam bathymetry observations; In order to be with the first The standardized residuals of the water depth observations corresponding to the solution results of the next iteration are calculated as follows:

[0031] (8)

[0032] In the formula, Representative and the The correction to the water depth observation value corresponding to the solution result of the next iteration; Representative and the The formula for calculating the unit weight error of the water depth observation correction corresponding to the solution result of the next iteration is:

[0033] (9)

[0034] In the formula, This represents the total number of water depth observations. The number of undetermined coefficients is given in formula (7). and Both are pre-set first control parameters and second control parameters;

[0035] The initial coefficient vector to be determined is solved based on formulas (5)-(9). When the set condition as shown in formula (10) is met, the iterative calculation process of the initial coefficient vector to be determined is stopped, and the equivalent weight is used to solve the problem. The corresponding sounding points were identified as suspicious gross errors in multibeam echo sounding, and these suspicious gross errors were marked.

[0036] (10).

[0037] Preferably, the method for constructing a multibeam bathymetry observation surface for seabed topography based on bathymetry data further includes:

[0038] Identify and mark suspicious gross errors in beamforming, and integrate them from... Multibeam bathymetry observations at each measuring point The original observation series of multibeam bathymetry were obtained. From the original observation series of multibeam bathymetry After removing suspicious gross errors in the beam sounding, a new series of multibeam sounding observations was obtained. Among them, multibeam bathymetry observation series The corresponding number of observations is ;

[0039] Will Treating them as observation vectors of equal precision, and following the same calculation process as formulas (1) to (4), determine the new series of observations. Corresponding coefficients of the surface function for seafloor topography:

[0040] (11)

[0041] In the formula, the first coefficient vector to be determined The dimension of the vector of initial coefficients to be determined is the same as that of the vector of initial coefficients to be determined. Same, still Coefficient matrix The dimension is ; The dimension is The first coefficient vector to be determined The corresponding seabed topographic trend surface can be obtained. for:

[0042] (12)

[0043] The seabed topographic trend surface determined by formula (12) It is called the multibeam bathymetry surface for seabed topography.

[0044] Preferably, when constructing the seabed topography multibeam bathymetry correction surface based on the bathymetry baseline data after gross error removal, the seabed topography multibeam bathymetry correction surface is constructed using the bathymetry baseline data after gross error removal, based on the lateral non-uniformity of multibeam bathymetry accuracy and the adaptive weighted least squares approximation principle. In this process, an adaptive weighting method is used to assign an adaptive weight factor related to the beam number to each bathymetry point, and the weighted least squares approximation principle is used to solve for the coefficients of the seabed topography polynomial or trigonometric polynomial.

[0045] Preferably, the adaptive weighting method assigns an adaptive weighting factor related to the beam number to each sounding point, including:

[0046] The adaptive weighting factor decreases continuously and nonlinearly as the beam number increases. The calculation formula is as follows:

[0047] (13)

[0048] In the formula, This is the beam number corresponding to the measurement point.

[0049] The maximum beam number for a single ping in multibeam echo sounding is The beam series on one side of the single ping is divided into 4 segments, the first segment being: Section 2 is: Section 3 is: Section 4 is: ,in, ,by Number and The beam number is used as the relative reference for weighting, and segmented weighting is performed according to the following principles:

[0050] Section 1 The weighting factor for beam # is:

[0051] (14)

[0052] Section 2 The weighting factor for beam # is:

[0053] , (15)

[0054] Section 3 The weighting factor for beam # is:

[0055] , (16)

[0056] Section 4 The weighting factor for beam # is:

[0057] , (17)

[0058] The series of depth values ​​after gross error removal Treating them as observation vectors of unequal precision, and following the same calculation process as formulas (1) to (4), determine the new series of observations. Corresponding coefficients of the surface function for seafloor topography:

[0059] (18)

[0060] In the formula, The unequal weight matrix of the observations, calculated by formula (13) or formulas (14)-(17), is given by the second coefficient vector to be determined. Another corresponding seafloor topographic trend surface can be obtained. for:

[0061] (19)

[0062] The seabed topographic trend surface determined by equation (18) It is called the seabed topography multibeam bathymetry correction surface.

[0063] Preferably, the method for calculating the surface difference between the multibeam bathymetry observation surface and the multibeam bathymetry correction surface for seabed topography includes:

[0064] Loading and constructing a multibeam bathymetry observation surface for seabed topography Multibeam bathymetry correction surface for seabed topography Calculate the multibeam bathymetry observation surface for seabed topography Multibeam bathymetry correction surface for seabed topography The difference is used to obtain the systematic bias correction for the water depth observations at each measuring point, i.e., the systematic bias correction for multibeam echo sounding:

[0065] (20)

[0066] In the formula, For the first The systematic bias correction for each water depth observation value at each measuring point is then calculated using the following formula for the series of multibeam echo sounding observation values ​​after gross error elimination. Perform system bias compensation:

[0067] (twenty one)

[0068] In the formula, The surface of the multibeam bathymetry results for seabed topography after systematic bias compensation, and... Corresponding seafloor topographic trend surface It is called a multibeam sounding compensation surface.

[0069] Compared with the prior art, the embodiments of this application have the following main advantages:

[0070] In this embodiment of the invention, three seabed topographic surfaces with different representational meanings (seabed topographic multibeam bathymetry observation surface, seabed topographic multibeam bathymetry correction surface, and seabed topographic multibeam bathymetry result surface) are constructed step by step. Through differential operations on the seabed topographic multibeam bathymetry observation surface and the seabed topographic multibeam bathymetry correction surface, the systematic deviation correction number for bathymetry is obtained. Ultimately, the predetermined goal of jointly detecting and compensating for gross errors and systematic deviations in multibeam bathymetry data is achieved. This method effectively solves the problem of jointly processing gross errors and systematic deviations in multibeam bathymetry data, significantly improves data quality, and enhances strip stitching effects. It has a particularly outstanding advantage in compensating for systematic deviations in deep-water areas or edge beams, providing strong technical support for obtaining high-precision and high-reliability seabed topographic models, and has significant value for widespread application.

[0071] In this embodiment of the invention, two adaptive weighting methods are based on adaptive weighting schemes for beam numbers (continuous nonlinear reduction model and piecewise weighting model). During the adjustment process, higher weights are assigned to the central high-precision beams and lower weights to the edge low-precision beams. This approach makes the constructed correction surface more reflective of the true measurement accuracy distribution, resulting in a more reasonable system deviation correction, especially in the edge beam region, where the compensation effect is superior to traditional methods. Attached Figure Description

[0072] Figure 1 This is a two-dimensional cross-sectional view of the original observation series of multibeam bathymetry in the multibeam measured area.

[0073] Figure 2 The image shows a two-dimensional cross-sectional view of the multibeam echo sounding observations after gross error removal.

[0074] Figure 3 The image shows a two-dimensional cross-sectional view of the multibeam bathymetry observation surface for seabed topography after gross error removal.

[0075] Figure 4 The image shows the two-dimensional cross-section of the seabed topography multibeam bathymetry correction surface after fitting using the adaptive weighting method.

[0076] Figure 5 The image shows a two-dimensional cross-sectional view of the surface of the multibeam bathymetry results for seabed topography after systematic bias compensation. Detailed Implementation

[0077] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0078] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0079] Currently, multibeam bathymetry results are affected by a combination of uncontrollable residual errors, including sound velocity profile measurement errors and their representative errors, installation angle observation errors, and attitude errors. To address these issues, we propose a comprehensive processing method that can complete the detection of gross errors and compensation for systematic errors in multibeam bathymetry in steps. This method involves jointly detecting gross errors and compensating for systematic biases. In short, the method first constructs a multibeam bathymetry observation surface based on bathymetry baseline data. Then, a multibeam bathymetry correction surface is constructed based on the bathymetry baseline data after gross error removal. The surface difference between the multibeam bathymetry observation surface and the correction surface is calculated to obtain the multibeam bathymetry systematic bias correction. Finally, the multibeam bathymetry systematic bias correction is subtracted from the bathymetry baseline data after gross error removal, resulting in the multibeam bathymetry result surface after gross error removal and systematic bias compensation. In this embodiment of the invention, three seabed topographic surfaces with different representational meanings (seabed topographic multibeam bathymetry observation surface, seabed topographic multibeam bathymetry correction surface, and seabed topographic multibeam bathymetry result surface) are constructed step by step. Through differential operations on the seabed topographic multibeam bathymetry observation surface and the seabed topographic multibeam bathymetry correction surface, the systematic deviation correction number for bathymetry is obtained. Ultimately, the predetermined goal of jointly detecting and compensating for gross errors and systematic deviations in multibeam bathymetry data is achieved. This method effectively solves the problem of jointly processing gross errors and systematic deviations in multibeam bathymetry data, significantly improves data quality, and enhances strip stitching effects. It has a particularly outstanding advantage in compensating for systematic deviations in deep-water areas or edge beams, providing strong technical support for obtaining high-precision and high-reliability seabed topographic models, and has significant value for widespread application.

[0080] This invention provides a multibeam bathymetry error processing method that jointly detects gross errors and compensates for system biases. Specifically, this method includes:

[0081] S10: Obtain the basic sounding data, select iterative robust filtering based on the trend surface, construct the seabed topography multibeam sounding observation surface based on the basic sounding data, perform gross error detection and removal on the basic sounding data through the seabed topography multibeam sounding observation surface, and output the basic sounding data after gross error removal.

[0082] S20, Load the bathymetry baseline data after gross error removal, and construct the seabed topography multibeam bathymetry correction surface based on the bathymetry baseline data after gross error removal;

[0083] S30, load the constructed seabed topography multibeam bathymetry observation surface and seabed topography multibeam bathymetry correction surface, calculate the surface difference between the seabed topography multibeam bathymetry observation surface and the seabed topography multibeam bathymetry correction surface, and obtain the multibeam bathymetry systematic deviation correction number;

[0084] S40, subtract the multibeam bathymetry systematic deviation correction from the bathymetry basic data after gross error removal, to obtain the seabed topography multibeam bathymetry result surface after gross error removal and systematic deviation compensation.

[0085] In this embodiment of the invention, three seabed topographic surfaces with different representational meanings (seabed topographic multibeam bathymetry observation surface, seabed topographic multibeam bathymetry correction surface, and seabed topographic multibeam bathymetry result surface) are constructed step by step. Through differential operations on the seabed topographic multibeam bathymetry observation surface and the seabed topographic multibeam bathymetry correction surface, the systematic deviation correction number for bathymetry is obtained. Ultimately, the predetermined goal of jointly detecting and compensating for gross errors and systematic deviations in multibeam bathymetry data is achieved. This method effectively solves the problem of jointly processing gross errors and systematic deviations in multibeam bathymetry data, significantly improves data quality, and enhances strip stitching effects. It has a particularly outstanding advantage in compensating for systematic deviations in deep-water areas or edge beams, providing strong technical support for obtaining high-precision and high-reliability seabed topographic models, and has significant value for widespread application.

[0086] In a further preferred embodiment of the present invention, the method for constructing a multibeam bathymetry observation surface for seabed topography based on bathymetry data includes:

[0087] S101, assuming that the seabed topographic surface and the multibeam echo sounder are both continuous smooth surfaces, and that isolated bathymetry data that deviate significantly from the sounder surface are considered gross errors, based on the above theoretical assumptions, seabed topographic data for the survey area are first acquired. Based on this data, the seabed topographic depth model is then constructed as a combination of a general polynomial and a trigonometric polynomial, where the combination of the general polynomial and the trigonometric polynomial is expressed as:

[0088] (1)

[0089] In the formula, The depth of the seabed topography; The latitude and longitude coordinates of the measurement points are used (with the lower left corner of the measurement area as the origin, and uniformly converted to angle minutes). , and The measurement blocks are located at the latitude line. and meridian Coverage range in the direction; where, generally, it is taken as:

[0090]

[0091]

[0092] , , , and For undetermined coefficients, the highest order and combination of the general polynomial and trigonometric polynomial in formula (1) are selected based on the seabed topographic data and bathymetry basic data of the survey area block. When selecting the highest order and combination of the general polynomial and trigonometric polynomial in formula (1) based on the seabed topographic data and bathymetry basic data of the survey area block, the topographic complexity of the survey area block can be determined based on the seabed topographic data of the survey area block, and the quality status of the multibeam bathymetry data can be determined through the bathymetry basic data. This allows for flexible selection of the highest order and combination of the general polynomial and trigonometric polynomial, letting... For the first The multibeam bathymetry observations at each measurement point have an observation error correction factor of [value missing]. Then we have:

[0093] (2)

[0094] Substitute formula (1) into formula (2), based on the measurement area... The following set of error equations is derived from the multibeam bathymetry observations:

[0095] (3)

[0096] In the formula, This is the correction vector for water depth observation errors; The coefficient matrix is ​​determined based on the coordinates of the measuring points and formula (1); For the reason undetermined coefficients , , , and The unknown vector formed; This is a vector of water depth observations;

[0097] S102, based on the principle of unequal precision least squares approximation, solve for the most probable solution of the undetermined coefficients, where the most probable solution of the undetermined coefficients in formula (3) is:

[0098] (4)

[0099] In formula (4), The weight matrix of the multibeam bathymetry observations;

[0100] Based on formula (4), the iterative solution of the unknown vector based on the equivalent weight robust estimation method is obtained as follows:

[0101] (5)

[0102] (6)

[0103] In the formula, To the initial weight matrix of the multibeam bathymetry observations and the first The equivalent weight matrix related to the residuals of the next iteration observations, and the size of its equivalent weight factor is determined by the IGGⅢ scheme;

[0104] S103, Calculate the equivalent weighting factor according to the IGGIII scheme, and identify and remove outliers based on the equivalent weighting factor;

[0105] The formula for calculating the equivalent weight factor according to the IGGIII scheme is as follows:

[0106] (7)

[0107] In the formula, The initial weighting factor for multibeam bathymetry observations can be uniformly set to 1; In order to be with the first The standardized residuals of the water depth observations corresponding to the solution results of the next iteration are calculated as follows:

[0108] (8)

[0109] In the formula, Representative and the The correction to the water depth observation value corresponding to the solution result of the next iteration; Representative and the The formula for calculating the unit weight error of the water depth observation correction corresponding to the solution result of the next iteration is:

[0110] (9)

[0111] In the formula, This represents the total number of water depth observations. The number of undetermined coefficients. , in formula (7) and Both are pre-set first and second control parameters. The typical value range for the first and second control parameters is as follows: (This embodiment takes) ); (This embodiment takes) );

[0112] The initial coefficient vector to be determined is solved based on formulas (5)-(9). When the set condition as shown in formula (10) is met, the iterative calculation process of the initial coefficient vector to be determined stops. The constraint mechanism of the set condition can be: when the solution of the unknown vector reaches a certain stability, it will be equivalent to the weight. The corresponding sounding points were identified as suspicious gross errors in multibeam echo sounding, and these suspicious gross errors were marked.

[0113] (10)

[0114] S104, identifies marked beamforming suspicious gross errors, and integrates them from... Multibeam bathymetry observations at each measuring point The original observation series of multibeam bathymetry were obtained. From the original observation series of multibeam bathymetry After removing suspicious gross errors in the beam sounding, a new series of multibeam sounding observations was obtained. Among them, multibeam bathymetry observation series The corresponding number of observations is , ;

[0115] S105, Treating them as observation vectors of equal precision, and following the same calculation process as formulas (1) to (4), determine the new series of observations. Corresponding coefficients of the surface function for seafloor topography:

[0116] (11)

[0117] In the formula, the first coefficient vector to be determined The dimension of the vector of initial coefficients to be determined is the same as that of the vector of initial coefficients to be determined. Same, still Coefficient matrix The dimension is ; The dimension is The first coefficient vector to be determined The corresponding seabed topographic trend surface can be obtained. for:

[0118] (12)

[0119] The seabed topographic trend surface determined by formula (12) It is called the multibeam bathymetry observation surface for seabed topography, or simply the observation surface.

[0120] In a further preferred embodiment of the present invention, when constructing the seabed topography multibeam bathymetry correction surface based on the bathymetry baseline data after gross error removal, the seabed topography multibeam bathymetry correction surface is constructed using the bathymetry baseline data after gross error removal, based on the lateral non-uniformity of multibeam bathymetry accuracy and the adaptive weighted least squares approximation principle. In this process, an adaptive weighting method is used to assign an adaptive weight factor related to the beam number to each bathymetry point, and the weighted least squares approximation principle is used to solve for the coefficients of the seabed topography polynomial or trigonometric polynomial.

[0121] In constructing the seabed topography multibeam bathymetry correction surface, it is assumed that the multibeam bathymetry accuracy varies with the beam point number sequence, and the observation accuracy generally decreases gradually from the central beam to the edge beams. Based on the above basic assumptions, the reliability of the bathymetry data is determined according to the beam number sequence, which is the adaptive weighting factor (influence weighting factor), and the seabed topography multibeam bathymetry correction surface is constructed based on this. First, the results of each multibeam bathymetry measurement point are represented as a four-dimensional data series (…). ),in, This refers to the beam number corresponding to the measuring point. Two schemes for calculating the influence factor of water depth observations based on the beam number of the measuring point are proposed here:

[0122] The first scheme assumes that the influence factor of the depth observation value decreases continuously and smoothly nonlinearly as the beam number of the measurement point increases. An adaptive weighting method is used to assign an adaptive weight factor related to the beam number to each depth measurement point. The first scheme includes:

[0123] The adaptive weighting factor decreases continuously and nonlinearly as the beam number increases. The calculation formula is as follows:

[0124] (13)

[0125] In the formula, This is the beam number corresponding to the measurement point.

[0126] On the other hand, the second scheme assumes that the influence factor of the depth observation value decreases piecewise, continuously, smoothly, linearly, and nonlinearly as the beam number of the measuring point increases. It employs an adaptive weighting method to assign an adaptive weight factor related to the beam number to each depth measuring point. The second scheme includes:

[0127] The maximum beam number for a single ping in multibeam echo sounding is The beam series on one side of the single ping is divided into 4 segments, the first segment being: Section 2 is: Section 3 is: Section 4 is: ,in, Assuming that the sounding point corresponding to the beam number in section 1 has the highest accuracy and uniform variation, section 2 has the next highest accuracy and non-uniform variation, section 3 has slightly lower accuracy than section 2 but uniform variation, and section 4 has the lowest accuracy and non-uniform variation, then... Number and The beam number is used as the relative reference for weighting, and segmented weighting is performed according to the following principles:

[0128] Section 1 The weighting factor for beam # is:

[0129] (14)

[0130] Section 2 The weighting factor for beam # is:

[0131] , (15)

[0132] Section 3 The weighting factor for beam # is:

[0133] , (16)

[0134] Section 4 The weighting factor for beam # is:

[0135] , (17)

[0136] The series of depth values ​​after gross error removal Treating them as observation vectors of unequal precision, and following the same calculation process as formulas (1) to (4), determine the new series of observations. Corresponding coefficients of the surface function for seafloor topography:

[0137] (18)

[0138] In the formula, The unequal weight matrix of the observations, calculated by formula (13) or formulas (14)-(17), is given by the second coefficient vector to be determined. Another corresponding seafloor topographic trend surface can be obtained. for:

[0139] (19)

[0140] The seabed topographic trend surface determined by equation (18) It is called the seabed topography multibeam bathymetry correction surface, or simply the correction surface.

[0141] In this embodiment, in practical applications, the beam number weighting scheme can be flexibly selected based on the characteristics of the instrument and equipment, sea conditions, and the changing characteristics of the strip data obtained in the field. The beam number segmentation method can be adjusted, and the value of the boundary beam number can be changed. Alternatively, the weighting formula of formula (14)-formula (17) can be improved based on the feedback of the system deviation compensation effect. Here, the two weighting schemes mentioned above are collectively referred to as adaptive weighting methods. The two adaptive weighting methods are based on the adaptive weighting scheme of beam number (continuous nonlinear reduction model and segmented weighting model). In the adjustment process, the central high-precision beam is given a higher weight, and the edge low-precision beam is given a lower weight. This processing method makes the constructed correction surface more reflective of the real measurement accuracy distribution, so the obtained system deviation correction number is more reasonable. Especially in the edge beam region, the compensation effect is better than the traditional method.

[0142] In a further preferred embodiment of the present invention, the method for calculating the surface difference between the seabed topography multibeam bathymetry observation surface and the seabed topography multibeam bathymetry correction surface includes:

[0143] Loading and constructing a multibeam bathymetry observation surface for seabed topography Multibeam bathymetry correction surface for seabed topography Theoretically speaking, the observation surface With correction surface The differences should be an objective reflection of the combined effects of the aforementioned residual errors. Based on this understanding, this method proposes to solve... and Difference between two surfaces to calculate the multibeam bathymetry observation surface for seabed topography. Multibeam bathymetry correction surface for seabed topography The difference is used to obtain the systematic bias correction for the water depth observations at each measuring point, i.e., the systematic bias correction for multibeam echo sounding:

[0144] (20)

[0145] In the formula, For the first The systematic bias correction for each water depth observation value at each measuring point is then calculated using the following formula for the series of multibeam echo sounding observation values ​​after gross error elimination. Perform system bias compensation:

[0146] (twenty one)

[0147] In the formula, The surface of the multibeam bathymetry results for seabed topography after systematic bias compensation, and... Corresponding seafloor topographic trend surface It is called the multibeam bathymetry compensation surface, or simply the compensation surface.

[0148] Combining the above methods, joint detection and compensation of gross errors and systematic biases in multibeam bathymetry were completed. Three seabed topographic surfaces with different characterization meanings were constructed, and corresponding bathymetry data results were obtained, including a series of multibeam bathymetry observations after gross error removal. The multibeam bathymetry trend surface model obtained by approximation through equal-precision adjustment The multibeam bathymetry observation surface of the seabed topography obtained by adaptive weighted adjustment approximation The surface of the multibeam bathymetry results for seabed topography after systematic bias compensation .

[0149] Numerical Verification and Analysis: In this embodiment, a small block covering 7 strips was selected from a multibeam echo sounder in a certain sea area as the numerical calculation test area. The coverage area is approximately 200m × 300m. The test area contains a total of 1,988,328 sounding points with a depth range of 17 to 27m. The depths were obtained by a Haizhuo MS8200 multibeam echo sounder, which has 512 beams. Figure 1 This is the original observation series of multibeam bathymetry for multibeam measured blocks (i.e., the original bathymetry basic data). The two-dimensional cross-section display effect diagram, from Figure 1 It can be seen that the dataset not only contains a certain number of outliers, but also shows a relatively obvious systematic deviation between adjacent strips. The variation characteristics of its detection signal due to external interference such as sound velocity profile, carrier attitude, and transducer installation error are extremely significant.

[0150] For the original multibeam bathymetry observation series of the multibeam measured block, the predefined seabed topographic trend surface function and the weighted iterative least squares method were first used to analyze the original multibeam bathymetry observation series of the aforementioned small block. Gross errors were detected and eliminated by segmenting the data, resulting in a series of multibeam bathymetry observations after filtering out contaminants. Statistics show that 15,921 abnormal bathymetry values ​​were detected in this small area (approximately 0.8% of the total measurement points). These are temporarily treated as gross errors and removed. Further analysis using multibeam bathymetry observation series... Based on the data, using the same seabed topographic trend surface function and equal-precision least squares method as described above, the seabed topographic multibeam bathymetry observation surface is obtained by strip-by-strip calculation. Multibeam bathymetry observation series Multibeam bathymetry observation surface for seabed topography The two-dimensional cross-section display effect diagram is as follows Figure 2 and Figure 3 As shown, comparison Figure 2 and Figure 1It can be seen that after gross error removal, there are no longer obvious isolated points and jump points in the multibeam bathymetry data, and the continuity and smoothness of the single strip data are improved to a certain extent.

[0151] Multibeam bathymetry observation series Using the basic data, the first scheme of the seabed topography trend surface function and adaptive weighting method was jointly used, along with the principle of unequal precision least squares method, to integrate the data from 7 strips and obtain the seabed topography multibeam bathymetry correction surface in one operation. Further research is needed on the multibeam bathymetry observation surface for seabed topography. Multibeam bathymetry correction surface for seabed topography The difference is used to obtain the systematic bias correction of the multibeam bathymetry system. The surface of the multibeam bathymetry results for seabed topography after systematic bias compensation is calculated according to formula (2). Seabed Topography Multibeam Bathymetry Correction Surface and the surface of the multibeam bathymetry results for seabed topography after systematic bias compensation The two-dimensional cross-section display effect diagram is as follows Figure 4 and Figure 5 As shown, comparison Figure 5 and Figure 2 It can be seen that after system bias compensation, the strip stitching effect and rationality of multibeam echo sounding data are significantly improved.

[0152] In summary, this invention provides a method for jointly detecting gross errors and compensating for systematic biases in multibeam bathymetry (MBS) data. In this embodiment, three seabed topographic surfaces with different representational meanings (a multibeam bathymetry observation surface, a multibeam bathymetry correction surface, and a multibeam bathymetry result surface) are constructed step-by-step. By performing differential operations on the multibeam bathymetry observation surface and the multibeam bathymetry correction surface, the correction value for systematic biases in bathymetry is obtained. Ultimately, the predetermined goal of jointly detecting and compensating for gross errors and systematic biases in multibeam bathymetry data is achieved. This method effectively solves the problem of jointly processing gross errors and systematic biases in multibeam bathymetry data, significantly improves data quality, and enhances strip stitching effects. It has a particularly significant advantage in compensating for systematic biases in deep-water areas or edge beams, providing strong technical support for obtaining high-precision, high-reliability seabed topographic models and possessing significant application value.

[0153] It should be noted that, for the sake of simplicity, the foregoing embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to the present invention. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0154] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on these embodiments, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still combine, add, delete, or otherwise adjust the features of the various embodiments of the present invention according to the circumstances without conflict or creative effort, thereby obtaining different technical solutions that do not fundamentally depart from the concept of the present invention. These technical solutions also fall within the scope of protection of the present invention.

Claims

1. A multi-beam bathymetry error processing method for detecting gross errors and compensating for systematic biases in combination, characterized in that, The method comprises: S10, acquiring sounding basic data, selecting iterative robust filtering based on a trend surface, constructing a seafloor topography multi-beam sounding observation surface based on the sounding basic data, detecting and eliminating gross errors of the sounding basic data through the seafloor topography multi-beam sounding observation surface, and outputting the sounding basic data after the gross errors are eliminated; S20, loading the sounding basic data after the gross errors are eliminated, and constructing a seafloor topography multi-beam sounding correction surface based on the sounding basic data after the gross errors are eliminated; S30, loading the constructed seafloor topography multi-beam sounding observation surface and the seafloor topography multi-beam sounding correction surface, calculating the surface difference value of the seafloor topography multi-beam sounding observation surface and the seafloor topography multi-beam sounding correction surface, and obtaining a multi-beam sounding systematic deviation correction number; S40, subtracting the multi-beam sounding systematic deviation correction number from the sounding basic data after the gross errors are eliminated, and obtaining a seafloor topography multi-beam sounding result surface after the gross errors are eliminated and the systematic deviation is compensated.

2. The multi-beam bathymetry error processing method of joint detection of gross errors and compensation of system biases of claim 1, wherein: The method for constructing the seafloor topography multi-beam sounding observation surface based on the sounding basic data comprises: acquiring seafloor topography data of a survey area block, modeling the seafloor topography depth into a combination of a general polynomial and a triangular polynomial based on the seafloor topography data of the survey area block, wherein the combination of the general polynomial and the triangular polynomial is expressed as: （1） In the formula, is the depth of the seabed topography; is the latitude and longitude coordinates of the measurement point; , and are the coverage of the measurement block in the latitude and longitude directions, respectively; wherein: , , , and For the coefficients to be determined, based on the seabed topographic data and bathymetry data of the survey area, select the highest order and combination of the general polynomial and trigonometric polynomial in formula (1), and let For the first The multibeam bathymetry observations at each measurement point have an observation error correction factor of [value missing]. Then we have: （2） Substitute equation (1) into equation (2), and list the error equations according to the multi-beam sounding observation values in the measurement block as follows: ​ （3） In the formula, is the error correction vector of the water depth observation; is the coefficient matrix determined according to the station coordinates and formula (1); is the unknown vector composed of undetermined coefficients , , , and ; is the water depth observation value vector; solving the most probable solution of the undetermined coefficients based on the principle of unequal-precision least squares approximation, wherein the most probable solution of the undetermined coefficients in formula (3) is: （4） In equation (4), is the weight matrix for the multibeam bathymetric observations; based on formula (4), obtaining an iterative solution of the unknown vector based on the equivalent weight robust estimation method as: （5） （6） In the formula, is the initial weight matrix of the multi-beam sounding observation value, and the first is the equivalent weight matrix related to the observation value residual of the second iteration of the IGG III scheme, and the size of the equivalent weight factor is determined by the IGG III scheme. calculating the equivalent weight factor according to the IGGIII scheme, and identifying and eliminating the gross error points based on the equivalent weight factor.

3. The multi-beam bathymetry error processing method of joint detection of blunders and compensation of system biases of claim 2, wherein: When the equivalent weight factor is calculated according to the IGGIII scheme, the calculation formula of the equivalent weight factor is expressed as: （7） wherein is the initial weight factor of the multibeam sounding observation value; is the water depth observation value corresponding to the first is the normalized residual error of the water depth observation value corresponding to the first iteration solution, and its calculation formula is: （8） In the formula, represent the water depth observation value correction number corresponding to the first iterative solution result; represent the water depth observation value correction number corresponding to the first iterative solution result; the unit weight error of the water depth observation value correction number is calculated by the formula: （9） In the formula, is the total number of water depth observation values; is the number of undetermined coefficients, and and are the first control parameter and the second control parameter respectively, which are set in advance. Solving the undetermined initial coefficient vector based on the formula (5) to formula (9), stopping the iteration process of the undetermined initial coefficient vector when the set condition such as formula (10) is met, and marking the suspicious coarse error point of the multi-beam sounding The corresponding sounding point is determined as a multi-beam sounding suspicious coarse error point, and the multi-beam sounding suspicious coarse error point is marked. （10）。 4. The multi-beam bathymetry error processing method of detecting and compensating for system biases of claim 3, wherein: The method for constructing the seafloor topography multi-beam sounding observation surface based on the sounding basic data further comprises: Identify suspicious beam sounding gross error points of the mark, integrate multiple beam sounding observations at a survey point , get the original observation series of multi-beam sounding , remove the suspicious beam sounding gross error points from the original observation series of multi-beam sounding , get the new observation series of multi-beam sounding , wherein the observation series of multi-beam sounding corresponding to the number of observations is ;​ The The trend surface function coefficients corresponding to the new series of observations are determined as equal-precision observation vectors according to the same calculation process as formulas (1)-(4). The trend surface function coefficients corresponding to the new series of observations are determined as equal-precision observation vectors according to the same calculation process as formulas (1)-(4). （11） In the formula, the first coefficient vector to be determined The dimension of the vector of initial coefficients to be determined is the same as that of the vector of initial coefficients to be determined. Same, still Coefficient matrix The dimension is ; The dimension is The first coefficient vector to be determined The corresponding seabed topographic trend surface can be obtained. for: （12） The sea floor topographic trend surface determined from equation (12) is called the sea floor topographic multi-beam sounding observation surface.

5. The multi-beam bathymetry error processing method of detecting and compensating for system biases of claim 4, wherein: When the seafloor topography multi-beam sounding correction surface is constructed based on the sounding basic data after the gross errors are eliminated, the seafloor topography multi-beam sounding correction surface is constructed by using the sounding basic data after the gross errors are eliminated, according to the multi-beam sounding precision lateral non-uniform characteristics and the principle of adaptive weighting least squares approximation, wherein the adaptive weighting method is used to give each sounding point an adaptive weight factor related to the beam number, and the weighted least squares approximation principle is used to solve the seafloor topography polynomial or triangular polynomial coefficients.

6. The multi-beam bathymetry error processing method of detecting and compensating for system biases of claim 5, wherein: The method for giving each sounding point an adaptive weight factor related to the beam number by using the adaptive weighting method comprises: The adaptive weight factor continuously and nonlinearly decreases with the increase of the beam number, and the calculation formula is: （13） In the formula, is the beam number corresponding to the measurement point.

7. The multi-beam bathymetry error processing method of detecting and compensating for system biases of claim 6, wherein: The method for giving each sounding point an adaptive weight factor related to the beam number by using the adaptive weighting method further comprises: The maximum beam number of single ping of multi-beam sounding is The beam series on one side of single ping is divided into 4 segments, the 1st segment is: ; the 2nd segment is: ; the 3rd segment is: ; the 4th segment is: , wherein, , the beam No. and the beam No. are the fixed weight relative reference The series of sounding values after the elimination of gross errors The series of sounding values after the elimination of gross errors The corresponding seabed topographic trend surface function coefficients: （18） In the formula, is the observation weight matrix calculated from the formula (13), and the second coefficient vector to be solved Another corresponding seafloor topographic trend surface can be obtained is: （19） the sea floor topography trend surface determined from equation (18) is called the sea floor topography multi-beam bathymetry correction surface.

8. The multi-beam bathymetry error processing method of detecting and compensating for system biases of claim 7, wherein: The method for calculating the surface difference value of the seafloor topography multi-beam sounding observation surface and the seafloor topography multi-beam sounding correction surface comprises: loading the constructed seafloor topography multibeam sounding observation surface and the seafloor topography multibeam sounding correction surface , calculating the difference between the seafloor topography multibeam sounding observation surface and the seafloor topography multibeam sounding correction surface , obtaining the systematic deviation correction number of each sounding point water depth observation value, that is, the multibeam sounding systematic deviation correction number: （20） In the formula, is the system bias correction number of the water depth observation value of the first measurement point, at this time, the system bias compensation is carried out on the multi-beam sounding observation value series after the gross error is eliminated according to the following formula: ​ （21） In the formula, is the multi-beam sounding result surface after system bias compensation, and the corresponding sea floor trend surface is called the multi-beam sounding compensation surface.

Images