Method and System for Attitude Correction of Ocean Buoy Observation Carrier Based on Multi-Antenna Beidou

Abstract

The present invention belongs to the technical field of ocean surveying, and discloses a method and system for attitude correction of an ocean buoy observation carrier based on multi-antenna Beidou. The method includes obtaining Beidou observation data of four Beidou receiver antennas on the buoy; after data preprocessing, eliminating gross errors and detecting cycle slips, adopting the kinematic differential mode to perform high-precision dynamic baseline vector solution to obtain the baseline vector values between the four Beidou receiver antennas; through prior constraint of baseline length and dynamic unconstrained network adjustment solution, detecting and weakening the gross error results in the baseline vectors to obtain the independent baseline vector results of the four Beidou receiver antennas; using the baseline vectors calculated in real time to obtain the current real-time attitude results; after performing buoy attitude correction based on the physical parameters of the buoy, obtaining precise buoy geodetic height observation results. The present invention improves the applicability and accuracy of ocean buoys under harsh sea conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of ocean measurement, and particularly relates to a method and system for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou. Background Art

[0002] With the rapid development of fields such as ocean scientific research and maritime transportation, ocean buoys, as important tools for ocean environment monitoring, are widely used in data collection tasks such as meteorology, oceanography, and environment.

[0003] The attitude of the buoy (including heading angle, pitch angle, and roll angle) has an important impact on the accuracy of the buoy's positioning, direction, and movement trajectory. However, due to the complexity of the buoy's working environment, including factors such as sea surface fluctuations, strong water currents, and the dynamic drift of the buoy itself, the attitude of the buoy is usually easily disturbed, resulting in a decrease in its attitude accuracy, and further affecting the reliability of the measurement results.

[0004] Currently, traditional methods for monitoring the attitude of ocean buoys mainly rely on single inertial measurement units (IMUs), gyroscopes, accelerometers, and other sensors to calculate the attitude. However, these sensors often have problems such as low accuracy, large drift, and sensitivity to environmental noise. In some extreme ocean environments, the error accumulation of these sensors will lead to serious deviations in the attitude, affecting the normal operation of the buoy.

[0005] In recent years, the application of the Beidou satellite navigation system in ocean measurement has gradually received attention. Beidou has a high-precision positioning function and can provide more accurate positioning data for ocean buoys. However, due to the frequent attitude changes of ocean buoys in a dynamic environment, a single Beidou receiver antenna cannot directly provide the real-time attitude information of the buoy. Therefore, how to use a Beidou receiver with multi-antenna distribution to obtain the carrier attitude and perform real-time attitude correction has become a key issue in the current accurate monitoring of the attitude of ocean buoys. Summary of the Invention

[0006] To overcome the problems existing in the related technologies, the disclosed embodiments of the present invention provide a method and system for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou, aiming to provide a low-cost, highly reliable, and high-precision ocean carrier attitude solution and correction system. By using low-cost multi-antenna Beidou devices, real-time high-precision absolute attitude measurement of marine carriers is achieved, greatly improving the operation efficiency and accuracy of marine carriers, reducing the regular maintenance cost of manpower, and improving the intelligent level of ocean operations.

[0007] To achieve the above object, the technical solution is as follows: A method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou includes the following steps:

[0008] S101. Use the BeiDou receivers in the BeiDou receiver data acquisition system to obtain the BeiDou observation data of the four BeiDou receiver antennas on the buoy; and receive the onshore BeiDou reference station data, perform differential positioning on the BeiDou main antenna on the buoy and the onshore BeiDou reference station data to obtain the differential positioning result of the buoy main antenna relative to the reference station.

[0009] S102. After the real-time BeiDou observation data of the buoy undergoes data preprocessing to eliminate gross errors and detect cycle slips, use the kinematic differential mode to perform high-precision dynamic baseline vector solution to obtain the initial values of the baseline vectors between the four BeiDou receiver antennas.

[0010] S103. According to the real-time obtained baseline network data of the four BeiDou receiver antennas, use the prior constraint of baseline length and dynamic unconstrained network adjustment solution to detect and weaken the gross errors and closure errors in the initial results of the baseline vector solution.

[0011] S104. Use the real-time baseline vector results between the antennas obtained by the four-antenna solution, and through coordinate transformation, obtain the real-time attitude angles of the current carrier in the heading, roll, and pitch directions.

[0012] S105. After performing buoy attitude correction based on the physical parameters of the buoy, obtain the precise buoy geodetic height observation results; based on the real-time three-dimensional attitude angle information of the GNSS system, provide real-time attitude correction values for the ocean buoy observation carrier to ensure the vertical measurement of the ocean water surface height by the equipment on the buoy carrier, correct the height error caused by the tilt of the buoy body due to the influence of waves and swells, and eliminate the systematic offset error caused by the attitude angle correction based on inertial equipment measurement.

[0013] In step S101, the BeiDou receiver data acquisition system includes: a buoy, a BeiDou receiver, BeiDou receiver antennas, a data acquisition module, and a power supply module.

[0014] Four BeiDou receivers are arranged on the buoy in a symmetric cross distribution, and the four BeiDou receivers are connected to four external BeiDou receiver antennas.

[0015] The data acquisition module performs data storage and data transmission.

[0016] The power supply module uses a combined power supply method of solar panels and storage batteries as the power supply system.

[0017] In step S102, obtaining the initial values of the baseline vectors between the four BeiDou receiver antennas includes:

[0018] S1021. For the collected BeiDou observation data, perform posterior processing on the gross errors by means of detection, identification, and adjustment.

[0019] S1022. For the Beidou observation data after rough inspection elimination, the cycle slip detection is carried out by using the dual-frequency code-phase combination method and the ionospheric residual method;

[0020] S1023. The kinematic differential mode is adopted to perform high-precision dynamic baseline vector solution to obtain the baseline vector values between four Beidou receiver antennas;

[0021] S1024. The ambiguity reduction correlation integer least squares estimation LAMBDA algorithm is adopted to solve the ambiguity and obtain the integer solution.

[0022] In step S1021, the posterior processing of the gross error is carried out by means of detection, identification, and adjustment, including:

[0023] In the detection stage, the data is tested by statistics, the redundant number and variance matrix of the observed values are calculated, and the chi-square test is used to judge whether there are abnormal data; if the test is significant, enter the identification step; if not, stop detection;

[0024] In the identification stage, the test statistic is constructed by the standardized residual. The test value exceeding the significance level indicates that a certain observed value is abnormal data. After removing this value, re-adjustment is carried out and overall inspection is carried out; if there are still abnormalities, continue to identify until the global inspection passes;

[0025] In the adjustment stage, the least squares estimation is carried out using the remaining observed values, and the final result is obtained and output.

[0026] In step S1023, the kinematic differential mode includes: using two Beidou receiver antennas installed on the moving carrier for differential processing, the coordinates of the Beidou receiver antenna as the reference station are not set to fixed values, and the results of real-time kinematic positioning are adopted; for the Beidou receiver as the rover station, differential processing is carried out with the reference station to solve and obtain the baseline vector of the rover station relative to the reference station;

[0027] The kinematic differential mode is adopted to perform high-precision dynamic baseline vector solution to obtain the baseline vector between four Beidou receiver antennas; in the double-difference observation model, at the same moment, the observation results of two receivers for the same satellite are differenced to eliminate the common errors between the receivers; the observations of the same receiver for two different satellites at two different times are differenced to eliminate the common errors between the satellites; the constructed satellite-station double-difference model is:

[0028] ;

[0029] ;

[0030] In the formula, is the satellite-station double-difference pseudorange observation value at time 𝑡, with the unit of meter, is the geometric distance of the satellite-station double difference at time 𝑡, is the ionospheric error of the satellite-station double difference at time 𝑡, is the tropospheric error of the satellite-station double difference at time 𝑡, is the other error term of the satellite-station double difference at time 𝑡, in meters, is the satellite-station double difference carrier phase observation value at time 𝑡, in cycles, is the satellite-station double difference value of the cycle ambiguity determined at the initial epoch 𝑡_0, in cycles, are the rover station and non-reference satellite numbers respectively, are the reference station and reference satellite numbers respectively, is the original pseudorange observation from the satellite to the receiver, in meters; is the spatial geometric distance from the satellite to the receiver, in meters; are the ionospheric and tropospheric errors respectively, is the other error, is the integer cycle ambiguity value in the carrier phase observation value, in cycles; is the wavelength of the frequency.

[0031] In step S1024, the reduced correlation integer least squares estimation LAMBDA algorithm for the cycle ambiguity is adopted to solve the ambiguity and obtain the integer solution, including: converting the variance-covariance matrix of the floating-point solution ambiguity value to achieve integer reduced correlation, weakening the correlation between the floating-point solution ambiguities, reducing the ambiguity search space, and achieving fast ambiguity fixation; the specific steps are:

[0032] (a) Under the condition of no external constraints, the Beidou double difference observations obtained by solving multiple baselines using the least squares method through the double difference observation data are used to obtain the parameter solution and and the cofactor matrix , and the Beidou double difference observation equations obtained from multiple baselines are:

[0033] ;

[0034] ;

[0035] In the formula, is the observation equation, is the unknown double difference parameter of the baseline, , is the unknown double difference parameters of the is the unknown parameter of the baseline length, , is the unknown baseline length parameter of the is The unknown double-difference parameter matrix of the baseline is The matrix containing baselines is the covariance of the observation vector is the covariance matrix of the observed quantities; , is The code and phase linearized observation vectors of the baselines is The ambiguity coefficient matrix of is The mapping matrix of is the cofactor matrix between baselines is the cofactor matrix of pseudorange and phase is product;

[0036] (b) Construct the ambiguity search to obtain the optimal problem, and the expression is:

[0037] ;

[0038] ;

[0039] In the formula, is the optimal integer ambiguity solution is the dimension of the search space is the vectorization operation of the matrix is the floating-point ambiguity solution is the weighted Euclidean norm, which measures and The weighted distance between is the constraint set, representing the set of all possible ambiguity solutions is a given constant used to define the size of the search space;

[0040] Through the search condition Under the constraint of The ambiguity vector closest to

[0041] (c) The LAMBDA algorithm performs Gaussian orthogonal transformation on the initial and the floating-point ambiguity solution to reduce the internal correlation of the floating-point solution ambiguity, perform correlation reduction processing on the floating-point solution, and finally obtain the integer solution;

[0042] ; ; In the formula, is the integer ambiguity vector obtained through transformation is the orthogonal transformation matrix The transpose of is an orthogonal transformation matrix The transpose of is an integer ambiguity vector The covariance matrix of is an orthogonal integer transformation matrix with a modulus value of 1, and the off-diagonal elements of after transformation are less than or equal to 0.5;

[0043] (d) Inspection and back substitution of integer ambiguities, using a significance ratio test, setting a threshold value, and testing the ratio of the second smallest value to the smallest value of If the test value is greater than the threshold, the ambiguity search is correct;

[0044] ;

[0045] In the formula, is the second smallest value of the objective function value, is the smallest value of the objective function value, and the optimal integer ambiguity solution The objective function value of is a pre-set threshold, and its value range is generally 2 to 3;

[0046] Then it is considered that The corresponding integer ambiguity value is the correct ambiguity combination.

[0047] In step S103, according to the four Beidou receiver antenna baseline network data obtained in real time, using the prior constraint of baseline length and dynamic unconstrained network adjustment solution, detecting and weakening the gross errors and closure errors in the initial value results of baseline vector solution, and obtaining four high-precision and high-reliability independent baseline vector results of Beidou receivers; specifically including:

[0048] S1031, Dynamic baseline solution based on baseline length constraint;

[0049] The measured value of the added pseudo-measurement equation , the measurement equation , the observation matrix , and the covariance of the measurement noise are respectively:

[0050] ;

[0051] ;

[0052] ;

[0053] ;

[0054] In the formula, is the baseline length, is the position of the rover station, is the signal reception time, is the position of the base station, is the error of the baseline length, represents transpose;

[0055] S1032, dynamic baseline solution based on dynamic unconstrained network adjustment solution;

[0056] According to the error equation, the datum equation, and the equation-covariance matrix, perform adjustment solution according to the least squares principle to obtain the adjusted result:

[0057] ;

[0058] In the formula, is the parameter correction after adjustment, is the coefficient matrix, is the transpose, is the covariance matrix of the observations of the inverse matrix, is the coefficient matrix of the datum equation, is the error vector of the observations;

[0059] The coordinates of each point after adjustment are expressed as:

[0060] ;

[0061] In the formula, is the initial coordinate value before adjustment;

[0062] The mean square error of unit weight after adjustment is:

[0063] ;

[0064] In the formula, is the number of baselines forming the Beidou network, is the total number of survey stations participating in the adjustment, is the mean square error of unit weight, is the correction vector.

[0065] In step S104, use the real-time baseline vector result between antennas obtained by four-antenna solution, and through coordinate transformation, obtain the real-time attitude angles of the current carrier in the heading, roll, and pitch directions; including:

[0066] S1041, the relationship between the baseline vector in the vehicle coordinate system and the navigation coordinate system;

[0067] ;

[0068] In the formula, are the baseline vectors of the baseline in the navigation coordinate system and the vehicle coordinate system respectively, is the attitude transformation matrix from the vehicle coordinate system to the navigation coordinate system;

[0069] S1042, directly solve the approximate values of the heading angle, pitch angle and roll angle , , ;

[0070] S1043, through the relationship of rotation transformation, use the least squares method for attitude calculation to obtain the attitude information of the vehicle.

[0071] In step S105, after correcting the buoy attitude based on the buoy physical parameters, obtain the precise buoy geodetic elevation observation results, including:

[0072] S1051, based on the data of the onshore Beidou reference station, form a dynamic solution of the baseline with the multi-antenna of the offshore buoy to obtain the instantaneous geodetic elevation of the phase center of the buoy Beidou main antenna ;

[0073] S1052, perform attitude calculation based on the dynamic baseline vector between the Beidou receivers' antennas to obtain the tilt angle of the buoy body , given the roll angle and pitch angle on the buoy vehicle, assuming unit vectors in the roll angle, pitch angle and heading angle directions, then the coordinate vectors of the unit vectors in the roll angle and pitch angle directions in the vehicle coordinate system are:

[0074] ;

[0075] ;

[0076] In order to estimate the tilt angle of the buoy vehicle, determine the angle between the normal line of the plane where the roll angle and pitch angle unit vectors are located and the plumb line, then the direction vector and the normal vector satisfy the relationship:

[0077] ;

[0078] Define the vector in the plumb line direction as , then add the condition here, make the axis direction of the normal vector positive and its value is 1; obtain the normal vector , the included angle between the normal vector and is the tilt angle of the buoy vehicle , the expression is:

[0079] ;

[0080] In the formula, is the vector in the direction of the plumb line;

[0081] S1053, according to the measurement results, perform the calibration of the multi-antenna Beidou sea surface height The calibration formula of the sea surface height is expressed as:

[0082] ;

[0083] In the formula, is the instantaneous geodetic elevation of the phase center of the Beidou main antenna of the buoy, is the height from the phase center of the Beidou receiver antenna to the water surface.

[0084] Another object of the present invention is to provide an attitude correction system for an ocean buoy observation carrier based on multi-antenna Beidou. This system implements the attitude correction method for an ocean buoy observation carrier based on multi-antenna Beidou. This system includes:

[0085] The Beidou receiver data acquisition system is used to deploy Beidou receiver equipment and perform the acquisition of observation data to obtain observation data; and receive the data of the onshore Beidou reference station, and perform differential positioning on the Beidou main antenna on the buoy and the data of the onshore Beidou reference station to obtain the differential positioning result of the buoy main antenna relative to the reference station;

[0086] The Beidou dynamic baseline precise processing module uses the kinematic differential mode to solve the baseline vectors of four Beidou receiver antennas; according to the baseline network data of the four Beidou receiver antennas obtained in real time, through the prior constraint of the baseline length and the dynamic unconstrained network adjustment solution, detect and weaken the gross error results in the baseline vectors, and obtain the independent baseline vector results of the four Beidou receiver antennas with high precision and high reliability;

[0087] The buoy attitude precise estimation and correction module obtains the current real-time attitude result by using the baseline vectors calculated in real time; the buoy attitude result determined by the baseline vectors undergoes initial attitude correction to eliminate the relative initial attitude error caused by the installation between the baseline network and the observation carrier platform; using the precise buoy attitude result obtained by the baseline network, correct the elevation error caused by the attitude of the buoy to obtain the precise ocean buoy observation result after attitude correction

[0088] Combining all the above technical solutions, the beneficial effects of the present invention are as follows: The present invention proposes a precise attitude correction system and method for ocean buoys based on multi-antenna Beidou, which performs buoy attitude correction to obtain precise buoy geodetic elevation observation results, weakens the influence of complex sea conditions on the buoy altimetry results, and improves the applicability and accuracy of ocean buoys under harsh sea conditions.

[0089] The present invention is used for the precise calibration of the attitude of ocean buoys. It mainly consists of a Beidou receiver data acquisition system, a precise processing module for Beidou dynamic baselines, and a precise estimation and correction module for the carrier attitude. The observation data of four Beidou receiver antennas on the carrier are obtained by using all-weather, real-time, and high-precision Beidou receivers. The Beidou receiver antennas are distributed symmetrically in a cross shape to obtain the maximum baseline length on a narrow observation platform as much as possible. After the Beidou observation data undergoes data preprocessing to eliminate gross errors and detect cycle slips, a kinematic differential mode is used for high-precision dynamic baseline vector solution to obtain the baseline vector values between the four Beidou receiver antennas. According to the real-time obtained baseline network data of the four Beidou receiver antennas, through prior constraint of baseline length and dynamic unconstrained network adjustment solution, the gross error results in the Beidou baseline vectors are detected and weakened to obtain high-precision and highly reliable independent baseline vector results of the four Beidou receiver antennas. The current real-time attitude result is obtained by using the baseline vectors calculated in real time. Based on the design parameters of the buoy observation carrier, attitude correction is performed to obtain precise ocean buoy observation results after attitude correction, weakening the influence of complex sea conditions on the observation platform results of the buoy carrier, and improving the applicability of ocean buoys under harsh sea conditions.

[0090] The present invention adopts low-cost Beidou receivers and improved algorithms, which greatly reduce the equipment cost and maintenance cost on the premise of ensuring accuracy, effectively extend the service life of the equipment, and effectively reduce the maintenance cost of ocean equipment. It greatly promotes the application of low-cost buoys in ocean observation and promotes the development of ocean economic activities. Compared with traditional inertial devices, absolute attitude information is obtained, providing a high-precision and highly reliable attitude observation system for domestic ocean equipment, obtaining precise ocean buoy observation results after attitude correction, weakening the influence of complex sea conditions on the observation platform results of the buoy carrier, and improving the applicability of ocean buoys under harsh sea conditions. Description of the Drawings

[0091] The drawings here are incorporated into the specification and form a part of this specification, showing the embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure;

[0092] Figure 1 It is a flow chart of the method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou provided by an embodiment of the present invention;

[0093] Figure 2Schematic diagram of the attitude correction system for the ocean buoy observation carrier based on multi-antenna Beidou provided by an embodiment of the present invention;

[0094] Figure 3 Principle diagram of the attitude correction method for the ocean buoy observation carrier based on multi-antenna Beidou provided by an embodiment of the present invention;

[0095] Figure 4 Schematic diagram of four receivers symmetrically installed in a cross on the buoy provided by an embodiment of the present invention;

[0096] Figure 5 Schematic diagram of the carrier coordinate system provided by an embodiment of the present invention;

[0097] In the figure: 1. Beidou receiver data acquisition system; 2. Beidou dynamic baseline precision processing module; 3. Buoy attitude precise estimation and correction module. Specific implementation manner

[0098] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the specific implementation manner of the present invention in detail with reference to the accompanying drawings. Many specific details are set forth in the following description to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific implementations disclosed below.

[0099] The innovation points of the present invention are as follows:

[0100] (1) The present invention is used for the precise calibration of the ocean buoy attitude, mainly composed of a Beidou receiver data acquisition system, a Beidou dynamic baseline precision processing module, and a carrier attitude precise estimation and correction module. The observation data of four Beidou receiver antennas on the carrier are obtained by using the all-weather, real-time, and high-precision Beidou receiver, and the high-precision dynamic baseline vector is obtained by using the kinematic differential mode;

[0101] (2) According to the baseline network data of the four Beidou receiver antennas obtained in real time, through the prior constraint of the baseline length and the dynamic unconstrained network adjustment solution, the accuracy of the baseline vector solution is improved, and the gross error results are detected and eliminated, providing high-precision and highly reliable baseline vector observation values for attitude measurement, and obtaining the high-precision three-dimensional attitude values of the carrier in real time;

[0102] (3) Using the current real-time attitude result, based on the design parameters of the buoy observation carrier, the buoy attitude correction is carried out to obtain the precise ocean buoy observation result after attitude correction, weakening the influence of complex sea conditions on the result of the buoy carrier observation platform, and improving the applicability of the ocean buoy in bad sea conditions.

[0103] Embodiment 1, as Figure 1As shown in the figure, the method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou provided by the embodiment of the present invention includes:

[0104] S101. Using the Beidou receivers in the Beidou receiver data acquisition system, obtain the Beidou observation data of the four Beidou receiver antennas on the buoy; and receive the Beidou reference station data on shore, perform differential positioning on the Beidou main antenna on the buoy and the Beidou reference station data on shore, and obtain the differential positioning result of the buoy main antenna relative to the reference station.

[0105] Using the Beidou receivers in the all-weather, real-time, and high-precision Beidou receiver data acquisition system to obtain the Beidou observation data of the four Beidou receiver antennas on the buoy; the Beidou receiver data acquisition system includes a buoy, a Beidou receiver, a Beidou receiver antenna, a data acquisition module, and a power supply module.

[0106] Four Beidou receivers are arranged on the buoy in a symmetric cross distribution and fixed. The four Beidou receivers are connected to four external Beidou receiver antennas.

[0107] The data acquisition module performs data storage and data transmission.

[0108] The power supply module uses a combined power supply method of a solar panel and a storage battery as the power supply system.

[0109] S102. After the real-time Beidou observation data of the buoy passes through data preprocessing, eliminates outliers and detects cycle slips, uses the kinematic differential mode to perform high-precision dynamic baseline vector solution, and obtains the initial value of the baseline vector between the four Beidou receiver antennas; specifically includes:

[0110] S1021. Perform posterior processing on the outliers in the collected Beidou observation data by the method of "detection - identification - adjustment".

[0111] S1022. Use the dual-frequency code-phase combination method and the ionospheric residual method to perform more rigorous cycle slip detection on the Beidou observation data after eliminating outliers.

[0112] S1023. Use the kinematic differential mode to perform high-precision dynamic baseline vector solution, and obtain the baseline vector value between the four Beidou receiver antennas.

[0113] S1024. Use the reduced correlation integer least squares estimation LAMBDA algorithm for integer ambiguity resolution to effectively solve the ambiguity and obtain an integer solution, which can greatly improve the accuracy of the baseline vector.

[0114] S103. According to the baseline network data of the four Beidou receiver antennas obtained in real time, use the prior constraint of the baseline length and the dynamic unconstrained network adjustment solution to detect and weaken the outliers and closure errors in the initial value result of the baseline vector solution.

[0115] The four-antenna design has more redundant observations, which can ensure that low-cost Beidou receiver devices provide stable and reliable GNSS positioning results. The network adjustment method is used to further improve the accuracy and reliability of the solution, and obtain the high-precision baseline vector value between Beidou antennas relative to the main antenna. Specifically, it includes:

[0116] S1031, dynamic baseline solution based on baseline length constraint;

[0117] S1032, dynamic baseline solution based on dynamic unconstrained network adjustment solution.

[0118] S104, using the real-time baseline vector results between antennas obtained by the four-antenna solution, through coordinate transformation, to obtain the real-time attitude angles of the current carrier in the heading, roll, and pitch directions;

[0119] Through the Beidou four-antenna method, the absolute attitude angle can be obtained quickly and with high precision, avoiding the problem that traditional inertial attitude devices will have large offsets during long-term operation and require regular maintenance and calibration of positioning, and effectively solving the maintenance problem of marine observation equipment. Specifically, it includes:

[0120] S1041, the relationship between the baseline vector in the carrier coordinate system and the navigation coordinate system;

[0121] ;

[0122] In the formula, are the baseline vectors of the baseline in the navigation coordinate system and the carrier coordinate system respectively, is the attitude transfer matrix from the carrier coordinate system to the navigation coordinate system;

[0123] S1042, directly solve the approximate values of the attitude angles (heading angle, pitch angle, and roll angle) 、 、 ;

[0124] S1043, through the relationship of rotation transformation, use the least squares method for attitude solution to obtain the attitude information of the carrier;

[0125] S105, after correcting the buoy attitude based on the physical parameters of the buoy, obtain the precise buoy geodetic elevation observation results; based on the real-time three-dimensional attitude angle information of the GNSS system, provide real-time attitude correction values for the marine buoy observation carrier, ensure the vertical measurement of the ocean water surface height by the equipment on the buoy carrier, correct the height error caused by the tilt of the buoy body due to waves and swells, and eliminate the systematic offset error caused by the attitude angle correction based on inertial equipment measurement; specifically, it includes:

[0126] S1051: Based on the data of the onshore Beidou reference station, dynamic solution of the baseline is performed with multiple antennas on the offshore buoy to obtain the instantaneous geodetic height of the phase center of the buoy's Beidou main antenna. ;

[0127] S1052: Perform attitude solution of the dynamic baseline vector between Beidou receivers' antennas to obtain the tilt angle of the buoy body. , Given the roll angle and pitch angle on the buoy carrier. Assuming there are unit vectors in the directions of roll angle, pitch angle and heading angle, the coordinate vectors of the unit vectors in the directions of roll angle and pitch angle in the carrier coordinate system are respectively:

[0128] ;

[0129] ;

[0130] To estimate the tilt angle of the buoy carrier, it is necessary to determine the angle between the normal line of the plane where the unit vectors of roll angle and pitch angle are located and the plumb line. Then the relationship between the direction vector and the normal vector satisfies:

[0131] ;

[0132] Define the vector in the plumb line direction as . Then add the condition here that the of the normal vector axis direction is positive and the value is 1; obtain the normal vector , and the angle between the normal vector and is the tilt angle of the buoy carrier, and the expression is:

[0133] ;

[0134] In the formula, is the vector in the plumb line direction;

[0135] S1053: According to the measurement results, calibrate the sea surface height of the multi-antenna Beidou. The sea surface height calibration formula is expressed as:

[0136] ;

[0137] In the formula, is the instantaneous geodetic height of the phase center of the buoy's Beidou main antenna, is the height from the phase center of the Beidou receiver antenna to the water surface.

[0138] As can be seen from the above embodiments, the present invention aims to obtain precise buoy geodetic elevation observation results after correcting the buoy attitude based on buoy physical parameters, weaken the influence of complex sea conditions on the buoy altimetry results, and improve the applicability of ocean buoys in adverse sea conditions.

[0139] Embodiment 2, as Figure 2 shown, the attitude correction system for ocean buoy observation carriers based on multi-antenna Beidou provided by the embodiments of the present invention includes: Beidou receiver data acquisition system 1, Beidou dynamic baseline precise processing module 2, and buoy attitude precise estimation and correction module 3.

[0140] The Beidou receiver data acquisition system 1 is used to deploy Beidou receiver equipment and collect observation data to obtain high-quality observation data (Beidou observation data) as much as possible;

[0141] The Beidou dynamic baseline precise processing module 2 uses the kinematic differential mode to solve the baseline vectors of four Beidou receiver antennas; according to the baseline network data of the four Beidou receiver antennas obtained in real time, through prior constraint of baseline length and dynamic unconstrained network adjustment, it detects and weakens the gross error results in the baseline vectors (Beidou baseline vectors) to obtain high-precision and highly reliable independent baseline vector results of the four Beidou receiver antennas;

[0142] The buoy attitude precise estimation and correction module 3 obtains the current real-time attitude result by using the baseline vectors calculated in real time; the buoy attitude result determined by the baseline vectors undergoes initial attitude correction to eliminate the relative initial attitude error caused by the installation between the baseline network and the observation carrier platform. Using the precise buoy attitude result obtained by the baseline network, it corrects the elevation error caused by the attitude of the buoy to obtain the precise ocean buoy observation result after attitude correction, weakens the influence of complex sea conditions on the observation results of the buoy carrier platform, and improves the applicability of ocean buoys in adverse sea conditions;

[0143] Exemplarily, the Beidou receiver data acquisition system includes a buoy, a Beidou receiver, a Beidou receiver antenna, a data acquisition module, and a power supply module;

[0144] The bottom of the buoy is designed with an anchor chain attachment, and the buoy is placed in a designated sea area for observation through the anchor chain to ensure that the buoy does not drift extensively.

[0145] The Beidou receiver is placed and fixed on the platform inside the buoy working cabin and is connected to four external Beidou receiver antennas through connecting wires. The four Beidou receiver antennas are arranged on the outer edge of the top platform of the buoy mast, showing a symmetric cross distribution and are fixed by metal connecting rods to ensure that the top is in an open and unobstructed environment.

[0146] The data acquisition module records the Beidou data observed by four Beidou receiver antennas and sends the Beidou data to the processor for processing.

[0147] The power supply module adopts a combined power supply method of solar panels and storage batteries. As a power supply system, the battery power ensures that the device can work continuously for 2 weeks without solar energy.

[0148] The Beidou dynamic baseline precise processing module 2 includes resolving the baseline vectors of four Beidou receiver antennas in the kinematic differential mode; according to the baseline network data of the four Beidou receiver antennas obtained in real time, through prior constraint of baseline length and kinematic unconstrained network adjustment, detecting and weakening the gross errors in the baseline vectors, and obtaining high-precision and highly reliable independent baseline vector results of the four Beidou receiver antennas.

[0149] The collected observation data processes the gross errors in the way of "detection - identification - adjustment".

[0150] For the observation data from which the gross errors have been removed, the dual-frequency code-phase combination method and the ionospheric residual method are added for more rigorous cycle slip detection.

[0151] The kinematic differential mode is used to perform high-precision dynamic baseline vector resolution to obtain the baseline vector values between four Beidou receiver antennas. The kinematic differential mode includes: using two Beidou receiver antennas installed on the moving carrier for differential processing, where the coordinates of the Beidou receiver antenna as the reference station are no longer set as fixed values, but the results of real-time kinematic positioning are adopted. The Beidou receiver as the rover station performs differential processing with the reference station to resolve the baseline vector of the rover station relative to the reference station.

[0152] Specifically, it includes: in the double-difference observation model, at the same moment, the observation results of two receivers for the same satellite are differenced to eliminate the common errors between the receivers. The observations of the same receiver for two different satellites at two different times are differenced to eliminate the common errors between the satellites. The constructed satellite-station double-difference model is:

[0153] ;

[0154] ;

[0155] In the formula, is the satellite-station double-difference pseudorange observation value at time 𝑡, with the unit of meter, is the satellite-station double-difference geometric distance at time 𝑡, with the unit of meter, is the satellite-station double-difference ionospheric error at time 𝑡, is the satellite-station double-difference tropospheric error at time 𝑡, Other error terms of the satellite-station double difference at time \(t\), unit: meter, Satellite-station double-difference carrier phase observation value at time \(t\), unit: cycle, Initial epoch Satellite-station double-difference value of the cycle ambiguity determined at the initial epoch, unit: cycle, Mobile station number and non-reference satellite number respectively, Reference station number and reference satellite number respectively, Original pseudo-range observation from satellite to receiver, unit: meter; Spatial geometric distance from satellite to receiver, unit: meter; Ionospheric error and tropospheric error respectively, Other error, Integer cycle ambiguity value in the carrier phase observation value, unit: cycle; Wavelength of the frequency.

[0156] Exemplarily, when using the carrier phase observation value to solve the ambiguity, the least-squares ambiguity decorrelation adjustment (LAMBDA) algorithm is adopted. By converting the variance-covariance matrix of the float ambiguity solution value, integer decorrelation is realized, the correlation between the float ambiguity solutions is weakened, the ambiguity search space is reduced, and rapid ambiguity fixing is achieved.

[0157] Exemplarily, the obtaining of the high-precision and high-reliability baseline vector results of four Beidou receiver antennas, which detects and weakens the gross error results in the Beidou baseline vector through baseline length prior constraint and dynamic unconstrained network adjustment solution based on the baseline network data of four Beidou receiver antennas obtained in real time, includes:

[0158] (1) Dynamic baseline solution based on baseline length constraint.

[0159] Measurement value of the added pseudo-measurement equation Measurement equation Observation matrix Covariance of the measurement noise Are respectively:

[0160] ;

[0161] ;

[0162] ;

[0163] ;

[0164] In the formula, Is the baseline length, Is the position of the mobile station, is the signal reception time, is the location of the base station, is the error of the baseline length, represents the transpose;

[0165] (2) Dynamic baseline solution based on dynamic unconstrained network adjustment solution.

[0166] According to the error equation, the reference equation, and the equation-covariance matrix, and performing adjustment solution according to the least squares principle, the adjusted result can be obtained:

[0167] ;

[0168] In the formula, is the parameter correction after adjustment, is the coefficient matrix, is the transpose, is the covariance matrix of the observed values inverse matrix of, is the coefficient matrix of the reference equation, is the error vector of the observed values;

[0169] The coordinates of each point after adjustment are expressed as:

[0170] ;

[0171] In the formula, is the initial coordinate value before adjustment;

[0172] The mean square error of unit weight after adjustment is:

[0173] ;

[0174] In the formula, is the number of baselines forming the Beidou network, is the total number of survey stations participating in the adjustment, is the mean square error of unit weight, is the correction vector.

[0175] Exemplarily, in the buoy attitude precise estimation and correction module 3, by using the real-time calculated baseline vector, the current real-time attitude result is obtained; the buoy attitude result determined by the baseline vector is corrected through the initial attitude to eliminate the relative initial attitude error caused by the installation between the baseline network and the observed carrier platform. The precise buoy attitude obtained by using the baseline network corrects the elevation error caused by the attitude of the buoy to obtain the precise ocean buoy observation result after attitude correction, specifically including:

[0176] (1)Based on the data of the onshore Beidou reference station, a dynamic solution is carried out for the baseline formed by multiple antennas on the offshore buoy to obtain the instantaneous geodetic height of the phase center of the buoy's Beidou main antenna ;

[0177] (2)Perform attitude solution for the dynamic baseline vector between Beidou receivers' antennas to estimate the tilt angle of the buoy body , given the roll angle and pitch angle on the buoy carrier. Assuming there are unit vectors in the directions of roll angle, pitch angle and heading angle, the coordinate vectors of the unit vectors in the directions of roll angle and pitch angle in the carrier coordinate system are respectively:

[0178] ;

[0179] ;

[0180] To estimate the tilt angle of the buoy carrier, it is necessary to determine the angle between the normal line of the plane where the unit vectors of roll angle and pitch angle are located and the plumb line. Then the relationship between the direction vector and the normal vector satisfies:

[0181] ;

[0182] Define the vector in the direction of the plumb line as . Then add the condition here that the axis direction of the normal vector is positive and its value is 1; obtain the normal vector , and the angle between the normal vector and is the tilt angle of the buoy carrier, and the expression is:

[0183] ;

[0184] (3)According to the measurement results, calibrate the sea surface height of the multi-antenna Beidou. The sea surface height calibration formula is expressed as:

[0185] ;

[0186] In the formula, is the instantaneous geodetic height of the phase center of the buoy's Beidou main antenna, is the height from the phase center of the Beidou receiver antenna to the water surface.

[0187] Example 3. Exemplarily, as another implementation manner of the present invention, as shown in Figure 3 , the method for correcting the attitude of the ocean buoy observation carrier based on multi-antenna Beidou includes:

[0188] S1. Use a Beidou receiver with all-weather, real-time, and high-precision capabilities to obtain the observation data of four Beidou receiver antennas on the buoy. The Beidou receiver antennas are arranged in a symmetric cross distribution to obtain the maximum baseline length on the narrow buoy platform as much as possible.

[0189] In step S1, assemble the Beidou receiver data acquisition system, including the buoy, Beidou receiver, four Beidou receiver antennas, data acquisition module, and power supply module, and complete the assembly of the entire system.

[0190] S11. Assemble the Beidou receiver data acquisition system: An anchor chain attachment is designed at the bottom of the buoy body. The buoy is placed in the designated sea area for observation through the anchor chain to ensure that the buoy does not drift significantly. The Beidou receiver is placed and fixed on the platform inside the buoy working cabin and is connected to the four external Beidou receiver antennas through connecting wires. The four Beidou receiver antennas are arranged on the outer edge of the top platform of the buoy mast, presenting a symmetric cross distribution, and are fixed by metal connecting rods to ensure that the top is in an open and unobstructed environment. The Beidou receiver antenna uses a choke antenna, and the device data is connected to the data acquisition module. As Figure 4 The schematic diagram of the four receiver antennas symmetrically cross-mounted on the buoy as shown;

[0191] S12. The data acquisition module includes: a data storage scheme and a data transmission scheme.

[0192] Data storage scheme: Use a TF card as the storage medium. The TF card has the advantages of low power consumption, small volume, and convenient replacement, and its writing speed fully meets the storage requirements.

[0193] Data transmission scheme: Adopt a wireless transmission method based on a 4G module, and at the same time reserve an RJ45 network port and a USART serial port. The provided network port can be connected to devices such as wired networks and wireless routers, and the USART serial port can be used for data debugging and external high-power radio stations and other devices.

[0194] Use the Beidou receiver to collect the original observation data of Beidou satellites, such as basic observables like pseudorange, carrier phase observations, and Doppler frequency shift, store the collected observation data, and complete data acquisition.

[0195] S13. Power supply module: Provide stable and continuous power. The power supply module adopts a 9 - 36V wide voltage design and uses a combination of solar panels and batteries for power supply to provide a single working voltage for the data acquisition system. The solar panel is installed on the side of the buoy platform, and a sealed battery compartment is installed on the side of the buoy. The battery compartment contains a maintenance-free battery, and its battery power ensures that the device can work continuously for 2 weeks without solar energy.

[0196] S2. After the Beidou observation data undergoes data preprocessing to eliminate gross errors and detect cycle slips, a kinematic differential mode is used to perform high-precision dynamic baseline vector calculation to obtain the baseline vector values between four Beidou receiver antennas.

[0197] S21. Under complex marine conditions, Beidou observations usually inevitably contain gross errors. The method of data detection is used to perform posterior processing on gross errors, which is specifically divided into the following three steps:

[0198] S211. Detection: The data is detected through statistics, and the redundant number of observations and its variance matrix are calculated. The chi-square test is used for hypothesis testing, and the significance level is set. If the test result is significant, it indicates that there are abnormal data in the observations, the alternative hypothesis holds, and it enters the further identification step; otherwise, if the test result is not significant, it indicates that there are no abnormalities in the data, the original hypothesis holds, and the detection process terminates.

[0199] S212. Identification: The test statistic is constructed through the standardized residual and calculated based on the residual and covariance matrix of the observed data. This test statistic follows the standard normal distribution. If the test result exceeds the critical value of the significance level, it indicates that the abnormal data is most likely to appear in a certain observation value. At this time, after removing this observation value, re-adjustment is performed, and the overall test statistic is used to determine whether there are still abnormal data. If abnormalities are found, continue with the identification step until it passes the global test.

[0200] S213. Adjustment: Finally, the remaining observations are used to re-perform the least squares estimation to obtain a reliable result and output it;

[0201] S22. The satellite signal is blocked by some obstacles and cannot reach the receiver, or due to external interference or the poor dynamic conditions of the receiver, the satellite signal is temporarily locked out, etc., which will cause cycle slip problems. The present invention uses the dual-frequency code-phase combination method and the ionospheric residual method to perform more rigorous cycle slip detection.

[0202] S23. A kinematic differential mode is used to perform high-precision dynamic baseline vector calculation to obtain the baseline vector values between four Beidou receiver antennas. Kinematic differential mode: Differential processing is performed using two antennas installed on a moving vehicle, and the coordinates of the base station are no longer set as fixed values. The mobile station continuously receives satellite signals and at the same time receives real-time satellite observation data from the mobile base station, and the baseline vector from the mobile station to the mobile base station is obtained through calculation; including:

[0203] S231. The Beidou kinematic differential positioning uses a double-difference observation model. At the same moment, the observation results of two receivers for the same satellite are differenced to eliminate the common errors between the receivers. The observation values of the same receiver for two different satellites at two different times are differenced to eliminate the common errors between the satellites.

[0204] S232, construct the satellite-station double-difference model;

[0205] S24, adopt the Least-Squares Ambiguity Decorrelation Adjustment (LAMBDA) algorithm to achieve rapid ambiguity fixing.

[0206] S241, under the condition of no external constraints, directly use the least-squares method to solve the Beidou double-difference observations obtained from multiple baselines to obtain the parameter solution and and the cofactor matrix , the Beidou double-difference observation equations obtained from multiple baselines are:

[0207] ;

[0208] ;

[0209] where is the observation equation, is the unknown double-difference parameter of the baseline, , is the unknown double-difference parameter matrix of the is the unknown parameter of the baseline length, , is the unknown baseline length parameter of the is the unknown double-difference parameter matrix of the is the matrix containing baselines, is the covariance of the observation vector, is the covariance matrix of the observed quantity; , is the code and phase linearized observation vector of the is the ambiguity coefficient matrix of the is the mapping matrix of the is the cofactor matrix between baselines, is the cofactor matrix of pseudorange and phase, is product;

[0210] S242, construct the ambiguity search to obtain the optimal problem:

[0211] ;

[0212] ;

[0213] In the formula, is the optimal integer ambiguity solution, is the dimension of the search space, is the vectorization operation of the matrix, is the floating-point ambiguity solution, is the weighted Euclidean norm, which measures and the weighted distance between them, is the constraint set, representing the set of all possible ambiguity solutions, is a given constant used to define the size of the search space;

[0214] Under the constraint of the search condition the ambiguity vector closest to ; since the search ellipsoid at this time approaches a long strip shape, the search radius is large, and there is a large amount of prepared ambiguity value data, reducing the efficiency of ambiguity search.

[0215] S243, the LAMBDA algorithm performs Gaussian orthogonal transformation on the initial and the floating-point ambiguity solution to reduce the internal correlation of the floating-point solution ambiguity, performs a series of correlation reduction processes on the floating-point solution, and finally obtains an integer solution.

[0216] ; ;

[0217] In the formula, is the integer ambiguity vector obtained by transformation, is the transpose of the orthogonal transformation matrix ; is the transpose of the orthogonal transformation matrix ; is the covariance matrix of the integer ambiguity vector ; is the orthogonal integer transformation matrix with a modulus value of 1, and the non-diagonal elements of after transformation are less than or equal to 0.5;

[0218] S244, the inspection and back substitution of the integer ambiguity: The significance ratio test is adopted, that is, a threshold value, called value, is set to test the ratio of the second smallest value to the smallest value. If the test value is greater than a certain threshold, it indicates that the ambiguity search is correct.

[0219] ;

[0220] In the formula, is the second smallest value of the objective function value, is the minimum value of the objective function value, the optimal integer ambiguity solution of the objective function value, is a preset threshold value, and its value range is generally from 2 to 3;

[0221] then it is considered that the corresponding integer ambiguity value is the correct ambiguity combination.

[0222] S25, the baseline solution is completed, and the baseline solution result outputs the independent baseline vector and its complete variance-covariance matrix.

[0223] Specifically, it can be expressed as:

[0224] ;

[0225] In the formula, , , respectively represent the variances of the obtained baseline vector in the three-axis directions, and the remaining elements represent the covariances.

[0226] S3, according to the baseline network data of the four Beidou receiver antennas obtained in real time, through the prior constraint of the baseline length and the dynamic unconstrained network adjustment solution, detect and weaken the gross error results in the Beidou baseline vector, and obtain the independent baseline vector results of the four Beidou receiver antennas with high precision and high reliability. Specifically, it includes:

[0227] S31, dynamic baseline solution based on baseline length constraint.

[0228] When constructing the observation equation of Beidou, add the baseline length constraint as a pseudo-measurement equation to improve the floating-point solution accuracy in a poor observation environment.

[0229] The measured value of the added pseudo-measurement equation , the measurement equation , the observation matrix , the covariance of the measurement noise are respectively:

[0230] ;

[0231] ;

[0232] ;

[0233] ;

[0234] In the formula, represents the baseline length, represents the position of the base station, Indicates the position of the rover station, Indicates the signal reception time, Indicates the error of the baseline length.

[0235] S32, Dynamic baseline solution based on dynamic unconstrained network adjustment.

[0236] S321, Error equation of Beidou network adjustment.

[0237] The observations used in the three-dimensional unconstrained adjustment of the Beidou network are all baseline vectors, that is, the coordinate differences from the starting point to the ending point of the baseline. Therefore, for each baseline vector, the following error equation can be listed

[0238] ;

[0239] In the formula, and respectively represent , The coordinates of the points, Indicates the , Baseline vector formed by the points obtained by baseline solution, Indicates the difference value between the baseline vector obtained by the difference of point coordinates and the baseline vector obtained by baseline solution, , Indicates the correction value.

[0240] S322, The present invention constructs the Beidou network benchmark equation by using the method of rank-deficient free network benchmark.

[0241] The rank-deficient free network benchmark is based on the centroid of the entire network. The coordinates of all stations are corrected according to the adjustment to obtain the corresponding correction values. Then the benchmark equation can be written as:

[0242] ;

[0243] In the formula: ;

[0244] S323, Observation weight matrix of Beidou network adjustment.

[0245] In the three-dimensional unconstrained adjustment of the Beidou network, the observation weight matrix of the baseline vector is usually determined by the variance-covariance matrix of each baseline vector obtained during baseline solution. The variance-covariance matrix can be obtained during baseline solution and can be specifically expressed as:

[0246] ;

[0247] In the formula, , , They respectively represent the variances of the obtained baseline vectors in the three-axis directions, and the remaining elements represent the covariances. After inverting the variance-covariance matrix, the weight matrix of the observations can be obtained. , that is:

[0248] ;

[0249] Using the covariance matrix and the weight matrix for network adjustment, the observations of all stations can be effectively integrated, improving the measurement accuracy and reducing errors. At the same time, it can also improve the efficiency and automation degree of data processing.

[0250] S324, least squares adjustment of the Beidou network.

[0251] According to the above error equations, reference equations, and variance-covariance matrix, and performing adjustment calculations according to the least squares principle, the adjusted results can be obtained:

[0252] ;

[0253] At this time, the coordinates of each point after adjustment can be expressed as:

[0254] ;

[0255] The mean square error of unit weight after adjustment:

[0256] ;

[0257] In the above formula, is the number of baselines forming the Beidou network, is the total number of survey stations participating in the adjustment.

[0258] So far, the detection and weakening of gross errors in the Beidou baseline vectors have been completed through prior constraints on baseline lengths and dynamic unconstrained network adjustment calculations, and the results of four independent baseline vectors of Beidou receiver antennas with high precision and high reliability have been obtained.

[0259] S4, using the baseline vectors calculated in real time to obtain the current real-time attitude results;

[0260] S41, the relationship between the position vectors of the same baseline in the vehicle coordinate system and in the navigation coordinate system reflects the rotational transformation relationship between the vehicle coordinate system and the navigation coordinate system. Through the rotational transformation relationship, attitude calculations are performed using the least squares method to obtain the attitude information of the vehicle.

[0261] The heading angle, pitch angle, and roll angle are respectively represented by , , are used to represent the angles of rotation about the Z-axis, X-axis, and Y-axis. The rotation is considered positive when it satisfies the right-hand rule and negative otherwise. Then, the three rotations can be represented by the attitude matrix in the following way:

[0262] ;

[0263] Then, the attitude angles can be represented as:

[0264] , , ;

[0265] S42, Establishment of the coordinate system.

[0266] According to geometric principles, three non-collinear points can determine a plane. Suppose there are four Beidou receiver antennas , , , , and the four antennas are symmetrically distributed in a cross shape. Pointing to is denoted as vector , Pointing to is denoted as vector . In the vehicle coordinate system, the baseline vector coincides with the Y-axis of the vehicle coordinate system, is located in the plane formed by the X-axis and the Y-axis, and the Z-axis is perpendicular to the plane formed by XY and points towards the zenith direction. The XYZ three axes form a right-handed coordinate system.

[0267] S43, Solving for the approximate values of the attitude angles (heading angle, pitch angle, and roll angle) based on the direct method , , ;

[0268] By performing baseline solution, the values of two baseline vectors and in the Earth-Centered Earth-Fixed (ECEF) coordinate system are obtained , . Taking as the origin, a local-level coordinate system (ENU) (coinciding with the local navigation coordinate system) is established, and the coordinates of , in the local-level coordinate system (ENU) are calculated and denoted as , .

[0269] The baseline vector in the ECEF coordinate system obtained through baseline length prior constraint and dynamic unconstrained network adjustment in S3 is transformed to the local coordinate system using the following formula:

[0270] ;

[0271] In the formula, is the baseline vector in the local coordinate system, is the local latitude, is the local longitude.

[0272] After obtaining the baseline vector and in the local coordinate system (ENU), the heading angle and pitch angle can be calculated using . The heading angle and pitch angle are respectively expressed as:

[0273] ; ;

[0274] For the baseline vector , the relationship between the vehicle coordinate system and the local coordinate system can be expressed as:

[0275] ; After obtaining the heading angle and pitch angle using the above formula, after arrangement, we can get:

[0276] ;

[0277] In the formula, , , are abbreviations, representing the baseline vector after two rotations.

[0278] After arrangement, we can get:

[0279] ;

[0280] Expanding the formula, the roll angle can be obtained:

[0281] ;

[0282] The approximate values of the solved attitude angles are marked as , , .

[0283] S44. Solving the attitude angles (heading angle, pitch angle, and roll angle) based on the least squares method of multiple antennas

[0284] For any baseline vector, the relationship between the vehicle coordinate system and the navigation coordinate system can be expressed as:

[0285] ;

[0286] The baseline vector in the vehicle coordinate system is known during installation. The baseline vector in the navigation coordinate system is obtained by solving the baseline vector, and solving the attitude is to solve the transformation matrix The three unknowns included 、 、 。

[0287] Set The antenna as the main antenna is the origin of the vehicle coordinate system. The baseline vector from the main antenna to other antennas in the vehicle coordinate system is , that is: 。

[0288] Bring 、 、 And substitute into After arrangement, the error equation can be expressed as:

[0289] ;

[0290] Linearize the above formula and further simplify to get:

[0291] ;

[0292] ;

[0293] In the formula, Is the covariance matrix of the observed value , and the other symbols are respectively expressed as:

[0294] ;

[0295] ;

[0296] ;

[0297] ;

[0298] ;

[0299] Then the estimated value of the attitude angle is:

[0300] ;

[0301] The covariance matrix is:

[0302] ;

[0303] Through multiple iterations of the least squares method until the correction value is smaller than the threshold value, and the iteration can be completed. The attitude angles (heading angle , pitch angle and roll angle ) are solved.

[0304] S45, determination of the mast tilt angle .

[0305] When the buoy attitude (heading angle , pitch angle and roll angle ) changes, the vertical height of the buoy mast also changes. The heading angle is related to the horizontal position or orientation of the object, but it does not directly affect the height in the vertical direction. The pitch angle and roll angle affect the height of the mast. These two angles are projected through vectors to obtain the mast tilt angle .

[0306] S5, after correcting the buoy attitude based on the buoy physical parameters, precise buoy geodetic elevation observation results are obtained, the influence of complex sea conditions on the buoy height measurement results is weakened, and the applicability of the ocean buoy under harsh sea conditions is improved.

[0307] S51, based on the data of the onshore Beidou reference station, a baseline dynamic solution is formed with the multi-antenna of the offshore buoy to obtain the instantaneous geodetic elevation of the phase center of the buoy Beidou main antenna ;

[0308] S52, multi-antenna Beidou buoy attitude solution, and the mast tilt angle of the buoy body is estimated.

[0309] In the above step S45, given the roll angle and pitch angle on the buoy carrier, assuming there are unit vectors in the directions of roll angle, pitch angle and heading angle, the coordinate vectors of the unit vectors in the directions of roll angle and pitch angle in the carrier coordinate system are respectively

[0310] ;

[0311] ;

[0312] wherein, the carrier coordinate system is as shown in Figure 5 .

[0313] In order to estimate the buoy carrier tilt angle, it is necessary to determine the angle between the normal line of the plane where the roll angle and pitch angle unit vectors are located and the plumb line. Then the direction vector and the normal vector satisfy the relationship:

[0314] ;

[0315] Define the vector in the direction of the plumb line as , then add the condition here that The Z-axis direction of is positive and the value is 1. Therefore, the normal vector is obtained.

[0316] Then the included angle between the normal vector and is the inclination angle of the buoy carrier, that is,

[0317] ;

[0318] S53. According to the above measurement results, calibrate the sea surface height of the multi-antenna buoy. The sea surface height calibration formula is expressed as:

[0319] ;

[0320] In the formula, is the height from the phase center of the Beidou receiver antenna to the water surface.

[0321] As described above, only the relatively optimal specific implementation manners of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for correcting the attitude of an ocean buoy observation carrier based on a multi-antenna Beidou, characterized in that: The method comprises the following steps: S101, using the Beidou receiver in the Beidou receiver data acquisition system, obtain Beidou observation data of four Beidou receiver antennas on the buoy; and receive data from the Beidou reference station on shore, perform differential positioning between the Beidou main antenna on the buoy and the Beidou reference station on shore, and obtain a differential positioning result of the buoy main antenna relative to the reference station; S102, the real-time Beidou observation data of the buoy is preprocessed to remove gross errors and detection cycle slips, and then a high-precision dynamic baseline vector solution is performed using a dynamic difference mode to obtain the initial value of the baseline vector between the four Beidou receiver antennas; S103, based on the baseline network data of four Beidou receiver antennas acquired in real time, using baseline length priori constraints and dynamic unconstrained network adjustment solution, detect and weaken gross errors and closure errors in the initial value results of baseline vector solution; S104, using the real-time baseline vector results between the four antennas calculated, through coordinate conversion, to obtain the real-time attitude angles of the current carrier in the heading, roll and pitch directions; S105, after buoy attitude correction based on the physical parameters of the buoy, obtain precise buoy geodetic height observation results; based on the real-time three-dimensional attitude angle information of the GNSS system, provide real-time attitude correction values ​​for the ocean buoy observation carrier, ensure the vertical measurement of the ocean surface height by the equipment on the buoy carrier, correct the height error caused by the tilt of the buoy body due to the influence of wave surges, and eliminate the systematic offset error caused by the attitude angle correction based on inertial equipment measurement.

2. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 1 is characterized in that: In step S101, the Beidou receiver data acquisition system includes: a buoy, a Beidou receiver, a Beidou receiver antenna, a data acquisition module and a power module; Four BeiDou receivers are deployed on the buoy in a symmetrical cross arrangement. The four BeiDou receivers are connected to four external BeiDou receiver antennas. The data acquisition module performs data storage and data transmission; The power module uses a combination of solar panels and batteries as the power supply system.

3. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 1 is characterized in that: In step S102, the initial value of the baseline vector between the four Beidou receiver antennas is obtained, including: S1021, for the collected Beidou observation data, the gross errors are processed a posteriori by means of detection, identification and adjustment; S1022: for the Beidou observation data that has been removed from the rough inspection, the dual-frequency code phase combination method and the ionospheric residual method are used to detect cycle slips; S1023, using the dynamic differential mode to perform high-precision dynamic baseline vector solution to obtain the baseline vector value between the four Beidou receiver antennas; S1024, using the integer ambiguity reduction correlation integer least squares estimation LAMBDA algorithm to resolve the ambiguity and obtain an integer solution.

4. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 3 is characterized in that: In step S1021, the gross errors are processed a posteriori by means of detection, identification, and adjustment, including: In the detection phase, the data is tested through statistics, the redundant number of observations and the variance matrix are calculated, and the chi-square test is used to determine whether there are abnormal data; if the test is significant, the identification step is entered; if not significant, the detection is stopped; In the identification stage, the test statistic is constructed by standardizing the residual. The test value exceeding the significance level indicates that a certain observation value is abnormal data. After removing the value, re-adjustment is performed and the overall test is performed. If there is still an abnormality, continue to identify until the global test passes. The adjustment phase uses the remaining observations to perform least squares estimation, and finally obtains the result and outputs it.

5. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 3 is characterized in that: In step S1023, the dynamic differential mode includes: using two Beidou receiver antennas installed on the moving carrier to perform differential processing, the coordinates of the Beidou receiver antenna as the reference station are not set to fixed values, and the results of real-time dynamic positioning are used; the Beidou receiver as the mobile station performs differential processing with the reference station to solve and obtain the baseline vector of the mobile station relative to the reference station; The dynamic differential mode is used to perform high-precision dynamic baseline vector solution to obtain the baseline vector between the four Beidou receiver antennas; in the double-difference observation model, at the same time, the two receivers perform differential observations of the same satellite to eliminate the common errors between the receivers; the same receiver performs differential observations of two different satellites at two different times to eliminate the common errors between the satellites; the constructed satellite station double-difference model is: ； ； In the formula, is the double-difference pseudo-range observation value of the satellite station at time 𝑡, in meters, is the double-difference geometric distance of the star station at time 𝑡, in meters, is the double-difference ionospheric error of the satellite station at time 𝑡, is the double-difference tropospheric error of the satellite station at time 𝑡, is the other error term of the double difference of the satellite station at time 𝑡, in meters, is the double-difference carrier phase observation value of the satellite station at time 𝑡, in weeks, Initial epoch The station double difference of the weekly ambiguity determined at time, in weeks, The rover and non-reference satellite numbers are are the reference station and reference satellite numbers, respectively. is the original pseudorange observation from the satellite to the receiver, in meters; is the spatial geometric distance from the satellite to the receiver, in meters; are the ionospheric and tropospheric errors, respectively. For other errors, is the integer ambiguity value in the carrier phase observation value, in weeks; is the wavelength of the frequency.

6. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 3 is characterized in that: In step S1024, the integer ambiguity reduction correlation integer least squares estimation LAMBDA algorithm is used to resolve the ambiguity and obtain an integer solution, including: converting the variance covariance matrix of the floating-point solution ambiguity value to achieve integer reduction correlation, weakening the correlation between the floating-point solution ambiguities, reducing the ambiguity search space, and achieving rapid ambiguity fixation; the specific steps are: (a) Without external constraints, the parameter solution is obtained by using the least squares method to solve the Beidou double-difference observations obtained from multiple baselines through double-difference observation data. and And the cofactor matrix , the Beidou double difference observation equation obtained from multiple baselines is: ； ； In the formula, is the observation equation, is the unknown double difference parameter of the baseline, , for The double difference parameters of the baseline are unknown; is the unknown parameter of the baseline length, , For the The unknown baseline length parameter of the baseline; for The unknown double difference parameter matrix of the baseline, for Contains The matrix of baselines, is the covariance of the observation vector, is the covariance matrix of the observations; , for Code and phase linearized observation vectors of the baseline; for The ambiguity coefficient matrix, for The mapping matrix, is the cofactor matrix between baselines, is the cofactor matrix of pseudorange and phase, for product; (b) Construct the optimal problem for fuzzy search, expressed as: ； ； In the formula, is the optimal integer ambiguity solution, is the dimension of the search space, is the vectorized operation of the matrix, is the floating point solution for the ambiguity, is the weighted Euclidean norm, which measures and The weighted distance between is a constraint set, representing the set of all possible ambiguity solutions, is a given constant used to define the size of the search space; By search criteria Under the constraint of The nearest blur vector; (c) The LAMBDA algorithm converts the initial and ambiguity float solution Perform Gaussian orthogonal transformation to reduce the internal correlation of the floating-point solution ambiguity, perform correlation reduction processing on the floating-point solution, and finally obtain an integer solution; ; ; In the formula, is the integer ambiguity vector obtained by transformation, is the orthogonal transformation matrix The transpose of is the orthogonal transformation matrix The transpose of is the integer ambiguity vector The covariance matrix of is an orthogonal integer transformation matrix with a modulus of 1, and after the transformation The off-diagonal elements of are less than or equal to 0.5; (d) Test and back-substitution of the integer ambiguity, using the significance ratio test and setting the threshold Value, test the ratio of the second smallest value to the smallest value , if the test value If it is greater than the threshold, the fuzzy search is correct; ； In the formula, is the second minimum value of the objective function, is the minimum value of the objective function, the optimal integer ambiguity solution The objective function value of It is a pre-set threshold, and its value range is generally 2 to 3; It is believed that The corresponding integer ambiguity value is the correct ambiguity combination.

7. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 1 is characterized in that: In step S103, based on the four Beidou receiver antenna baseline network data acquired in real time, the baseline length priori constraint and the dynamic unconstrained network adjustment solution are used to detect and weaken the gross errors and closure errors in the initial value results of the baseline vector solution, and obtain the four Beidou receiver antenna independent baseline vector results with high precision and high reliability; specifically, it includes: S1031, dynamic baseline solution based on baseline length constraint; Added pseudo-measurement equation measurement value , measurement equation , observation matrix , the covariance of the measurement noise They are: ； ； ； ； In the formula, is the baseline length, is the position of the rover, is the signal receiving time, is the location of the base station, is the error in the baseline length, represents transpose; S1032, dynamic baseline solution based on dynamic unconstrained network adjustment solution; According to the error equation, the reference equation and the equation-covariance matrix, the adjustment is performed according to the least squares principle to obtain the adjusted result: ； In the formula, is the parameter correction number after adjustment, is the coefficient matrix, For transposition, is the covariance matrix of the observations The inverse matrix of is the coefficient matrix of the benchmark equation, is the error vector of the observed value; Coordinates of each point after adjustment It is expressed as: ； In the formula, is the initial coordinate value before adjustment; The unit weighted mean error after adjustment is: ； In the formula, is the number of baselines that make up the Beidou network. is the total number of measuring stations involved in the adjustment, is the unit weight error, is the correction vector.

8. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 1, characterized in that: In step S104, the real-time baseline vector results between antennas obtained by solving the four antennas are used to obtain the real-time attitude angles of the current carrier in the heading, roll and pitch directions through coordinate conversion; including: S1041, relationship between baseline vector in carrier coordinate system and navigation coordinate system; ； In the formula, are the baseline vectors in the navigation coordinate system and the carrier coordinate system respectively, is the attitude transfer matrix from the carrier coordinate system to the navigation coordinate system; S1042, direct method to solve the approximate values ​​of heading angle, pitch angle and roll angle , , ; S1043, using the relationship of rotation transformation, the least square method is used to perform posture calculation to obtain the posture information of the carrier.

9. The method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou according to claim 1, characterized in that: In step S105, after the buoy attitude is corrected based on the buoy physical parameters, a precise buoy geodetic height observation result is obtained, including: S1051, based on the data of the BeiDou reference station on the shore, dynamically solves the baseline formed by the multi-antenna of the offshore buoy to obtain the instantaneous geodetic elevation of the phase center of the BeiDou main antenna of the buoy ; S1052: Perform attitude calculation based on the dynamic baseline vector between Beidou receiver antennas to obtain the tilt angle of the buoy , the roll angle on the buoy carrier is known and pitch angle , there are unit vectors in the directions of roll angle, pitch angle and heading angle, then the coordinate vectors of the unit vectors in the directions of roll angle and pitch angle in the carrier coordinate system are: ； ； In order to estimate the inclination angle of the buoy carrier, determine the angle between the normal line of the plane where the unit vectors of the roll angle and the pitch angle are located and the plumb line, then the direction vector With normal vector The relationship satisfies: ； The vector defining the direction of the plumb line is , then add a condition here, let the normal vector of The axis direction is positive and the value is 1; get the normal vector , the normal vector and The angle is the inclination angle of the buoy carrier , the expression is: ； In the formula, is the vector in the direction of the plumb line; S1053, based on the measurement results, multi-antenna Beidou sea level height The calibration formula of sea level height is expressed as: ； In the formula, is the instantaneous geodetic elevation of the phase center of the Beidou main antenna of the buoy, is the height from the phase center of the Beidou receiver antenna to the water surface.

10. A multi-antenna Beidou-based ocean buoy observation carrier attitude correction system, characterized in that: The system implements the method for correcting the attitude of an ocean buoy observation carrier based on multi-antenna Beidou as described in any one of claims 1 to 9, and the system comprises: The Beidou receiver data acquisition system (1) is used to deploy Beidou receiver equipment and collect observation data to obtain observation data; and receive data from a Beidou reference station on shore, perform differential positioning between the Beidou main antenna on the buoy and the Beidou reference station on shore, and obtain a differential positioning result of the buoy main antenna relative to the reference station; The Beidou dynamic baseline precision processing module (2) uses a dynamic differential mode to solve the baseline vectors of the four Beidou receiver antennas; based on the baseline network data of the four Beidou receiver antennas acquired in real time, the module detects and weakens the gross error results in the baseline vectors through baseline length prior constraints and dynamic unconstrained network adjustment and solves, thereby obtaining high-precision and high-reliability independent baseline vector results of the four Beidou receiver antennas; The buoy attitude precise estimation and correction module (3) obtains the current real-time attitude result by using the baseline vector calculated in real time; the buoy attitude result determined by the baseline vector is corrected by the initial attitude to eliminate the relative initial attitude error caused by the placement between the baseline network and the observation carrier platform; the precise buoy attitude result obtained by the baseline network is used to correct the elevation error caused by the buoy attitude, and obtain the precise ocean buoy observation result after attitude correction.

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