Single Beidou positioning-based ship wind measurement method, medium and system

Abstract

The invention provides a ship wind measurement method, medium and system based on single Beidou positioning, and belongs to the technical field of ship wind measurement, and the ship wind measurement method, medium and system based on single Beidou positioning comprises the steps: collecting the ship position and anemometer data through a Beidou system; carrying out component decomposition on the position data to obtain stable and variable components of the navigational speed and the navigational direction; decomposing the wind speed data to obtain stable and variable components of the wind speed; establishing a correlation function of navigational speed, course and wind speed change, and constructing a ship motion state matrix; calculating a ship velocity vector and converting a coordinate system; constructing an environment wind speed influence matrix; according to a state and influence matrix synthesis operation, calculating an actual wind speed vector, calculating a real wind direction angle, and solving through an optimal path matrix; calculating wind speed and wind direction error compensation amount, and applying the compensation amount to the actual wind speed vector and the actual wind direction angle to obtain corrected data; the measurement accuracy of the wind measurement system can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of ship wind measurement, and in particular, relates to a ship wind measurement method, medium and system based on single Beidou positioning. Background Art

[0002] Ship wind measurement technology is an important part of the navigation field. It can provide key meteorological information support for ship navigation and play an important role in improving navigation safety and efficiency. The existing ship wind measurement technology mainly includes two methods: ship wind measurement method based on multiple Beidou positioning receivers and ship wind measurement method based on external sensors.

[0003] The ship wind measurement method based on multiple Beidou positioning receivers uses two or three Beidou positioning receivers installed at different positions on the ship, and calculates the wind speed and direction by calculating the speed difference between these receivers. The advantage of this method is that it can use the high-precision position and speed data provided by the Beidou positioning system, without the need for additional sensors, and the measurement cost is low. However, since multiple positioning receivers need to be installed, and the positional relationship between these receivers will change with the movement of the ship, complex mathematical modeling and calculation are required, the overall complexity of the system is high, and there are certain technical difficulties in practical applications.

[0004] The ship wind measurement method based on external sensors usually installs a dedicated wind speed and direction sensor on the mast or side of the ship to directly measure the relative wind speed and relative wind direction. The data measured by this method is highly accurate, and the system structure is relatively simple and easy to implement. However, this method requires additional sensor equipment, which increases the system cost, and the installation position of the sensor is easily affected by the ship's navigation posture, thereby affecting the measurement accuracy. In addition, the relative wind speed and relative wind direction need to be converted using the ship's own speed and heading data to obtain the actual environmental wind conditions, which increases the complexity of the system.

[0005] In summary, the existing ship wind measurement technology has the problems of high cost, limited accuracy, high system complexity, etc. In view of these problems, the present invention proposes a ship wind measurement method based on single Beidou positioning, which uses the high-precision position and motion state data provided by the Beidou positioning system, combined with ultrasonic wind speed and direction sensors, and analyzes the influence of ship motion on wind speed, and establishes a coupling relationship model between ship motion state and ambient wind speed, thereby achieving high-precision measurement of real ambient wind conditions. Compared with the prior art, the wind measurement system of the present invention has the advantages of low cost, high measurement accuracy, simple system structure, etc., and provides a new technical solution for ship meteorological monitoring and navigation control. Summary of the invention

[0006] In view of this, the present invention provides a ship wind measurement method, medium and system based on single Beidou positioning, which can improve the measurement accuracy of the wind measurement system and provide a new solution for ship meteorological monitoring and navigation.

[0007] The present invention is implemented as follows: In a first aspect, the present invention provides a ship wind measurement method based on single Beidou positioning, comprising the following steps: collecting real-time position data of the ship and real-time data of anemometer through a Beidou positioning system; performing component decomposition operation on the real-time position data of the ship to obtain a stable speed component and a speed variation component of the ship speed data, and obtain a stable heading component and a heading variation component of the ship heading data; performing component decomposition operation on the real-time data of the anemometer to obtain a stable wind speed component and a wind speed variation component of the relative wind speed data; establishing a motion correlation function of the stable speed component, the stable heading component and the wind speed variation component, and constructing a ship motion state matrix; calculating the ship speed vector; constructing an environmental wind speed influence matrix; calculating the actual wind speed vector; calculating the true wind direction angle; calculating the wind speed error compensation amount and the wind direction error compensation amount, and obtaining corrected wind speed data and corrected wind direction data.

[0008] Among them, the step of collecting the real-time position data of the ship through the Beidou positioning system is specifically to use the Beidou positioning chip to receive the Beidou navigation satellite signal, and obtain the real-time longitude and latitude data of the ship through differential correction processing, and the sampling frequency of the real-time longitude and latitude data of the ship is 1 Hz; the Beidou positioning system speed measurement module is used to calculate the ship speed data; the Beidou positioning system heading measurement module is used to calculate the ship heading data; a dual-axis ultrasonic wind speed and direction sensor is used to construct an anemometer, and the relative wind speed data and relative wind direction data are calculated by measuring the ultrasonic propagation time difference between different sensors.

[0009] Among them, the step of performing component decomposition operation on the real-time position data of the ship specifically adopts a multi-scale wavelet decomposition method to process the ship speed data, selects the Doppler 4th-order wavelet function as the decomposition basis function, obtains the low-frequency component of the ship speed data as the speed stability component through a 4-layer wavelet decomposition, and uses the high-frequency component of the ship speed data as the speed variation component; uses the Fourier transform method to process the ship heading data; and uses the empirical mode decomposition method to process the relative wind speed data.

[0010] Among them, the step of establishing the motion correlation function of the speed stability component, the heading stability component and the wind speed variation component is specifically to establish the motion correlation function of the speed stability component, the heading stability component and the wind speed variation component based on the fluid mechanics theory, the motion correlation function includes trigonometric function terms and linear terms, and the coefficients of the trigonometric function terms and the linear term coefficients are calculated by the least squares method; the ship motion state matrix is ​​constructed according to the motion correlation function, and the ship motion state matrix is ​​a 3×3 matrix; and the ship motion state matrix is ​​subjected to singular value decomposition.

[0011] Among them, the step of calculating the ship speed vector is specifically to decompose the ship speed data into longitude speed component and latitude speed component based on the vector decomposition principle, and calculate the longitude speed component and the latitude speed component by trigonometric functions; consider the influence of the ship heading data to construct a rotation matrix, the rotation matrix contains the heading angle cosine term and the heading angle sine term; multiply the longitude speed component and the latitude speed component by the rotation matrix to obtain the ship speed vector in the geographic coordinate system.

[0012] Among them, the step of constructing the environmental wind speed influence matrix specifically constructs a 2×2 environmental wind speed influence matrix; calculates the wind speed influence coefficient, which is related to the wind speed size and the effective area, and is obtained by fitting the wind tunnel test data; calculates the wind direction influence coefficient, which is related to the wind direction angle and the shape of the ship, and is obtained by a numerical simulation method; and combines the wind speed influence coefficient and the wind direction influence coefficient into an environmental wind speed influence matrix.

[0013] Among them, the step of calculating the actual wind speed vector is specifically to convert the relative wind speed data and the relative wind direction data into a relative wind speed vector; multiply the environmental wind speed influence matrix with the relative wind speed vector to obtain the environmental influence wind speed vector; multiply the ship motion state matrix with the environmental influence wind speed vector to obtain the ship motion influence wind speed vector; synthesize the ship speed vector with the ship motion influence wind speed vector to obtain the actual wind speed vector; and use a Kalman filter to filter the actual wind speed vector.

[0014] Among them, the step of calculating the true wind direction angle is specifically to extract the longitude component and the latitude component of the actual wind speed vector; calculate the angle between the actual wind speed vector and the true north direction by the inverse tangent function to obtain the initial true wind direction angle; construct a 3×3 optimal path matrix, and optimize the optimal path matrix elements by the dynamic programming method; iteratively optimize the initial true wind direction angle based on the optimal path matrix; and correct the optimized wind direction angle by statistical analysis of historical data.

[0015] Specifically, the method of the present invention specifically comprises: S10, collecting real-time position data of the ship through the Beidou positioning system, the real-time position data of the ship including the longitude data of the ship, the latitude data of the ship, the speed data of the ship, and the heading data of the ship; collecting real-time data of the anemometer, the real-time data of the anemometer including the relative wind speed data and the relative wind direction data; S20, performing component decomposition operation on the real-time position data of the ship to obtain a stable speed component of the ship speed data and a speed variation component of the ship speed data, and obtaining a stable heading component of the ship heading data and a heading variation component of the ship heading data; performing component decomposition operation on the real-time data of the anemometer to obtain a stable wind speed component of the relative wind speed data and a wind speed variation component of the relative wind speed data; S30, establishing a motion correlation function of the speed stability component, the heading stability component and the wind speed variation component, and constructing a ship motion state matrix according to the motion correlation function, wherein the ship motion state matrix includes a ship speed contribution coefficient and a ship heading contribution coefficient; S40, calculating a ship velocity vector according to the ship motion state matrix, the ship velocity vector including a ship longitude velocity component and a ship latitude velocity component, and converting the ship velocity vector from a geographic coordinate system to a ship coordinate system; S50, constructing an environmental wind speed influence matrix, wherein the environmental wind speed influence matrix includes a wind speed contribution value of the relative wind speed data to the ship motion and a wind direction contribution value of the relative wind direction data to the ship motion; S60, performing matrix synthesis operation according to the ship motion state matrix and the environmental wind speed influence matrix to calculate an actual wind speed vector, wherein the actual wind speed vector is synthesized by the relative wind speed data and the ship speed vector; S70, calculating a true wind direction angle according to the actual wind speed vector, the true wind direction angle being the angle between the actual wind speed vector and the true north direction, and solving the true wind direction angle by performing an optimal path matrix operation; S80. Calculate the wind speed error compensation and the wind direction error compensation according to the ship motion state matrix and the environmental wind speed influence matrix, apply the wind speed error compensation and the wind direction error compensation to the actual wind speed vector and the true wind direction angle respectively, and obtain corrected wind speed data and corrected wind direction data.

[0016] On the basis of the above technical solution, the ship wind measurement method based on single Beidou positioning of the present invention can also be improved as follows: Among them, the step S10 specifically includes: using a Beidou positioning chip to receive Beidou navigation satellite signals, and obtaining real-time longitude and latitude data of the ship through differential correction processing, the sampling frequency of the real-time longitude and latitude data of the ship is 1 Hz, and the real-time longitude and latitude data of the ship includes longitude data and latitude data, the accuracy of the longitude data is better than 0.000001 degrees, and the accuracy of the latitude data is better than 0.000001 degrees; using the Beidou positioning system speed measurement module to calculate the ship speed data, and obtaining the ship speed data through speed factor calibration correction, the sampling frequency of the ship speed data is 1 Hz, and the accuracy of the ship speed data is Better than 0.1 meters per second; the Beidou positioning system heading measurement module is used to calculate the ship heading data, and the ship heading data is obtained through heading deviation calibration. The sampling frequency of the ship heading data is 1 Hz, and the accuracy of the ship heading data is better than 0.1 degrees; a dual-axis ultrasonic wind speed and direction sensor is used to construct an anemometer, and the relative wind speed data and relative wind direction data are calculated by measuring the ultrasonic propagation time difference between different sensors. The sampling frequency of the relative wind speed data is 10 Hz, and the accuracy of the relative wind speed data is better than 0.1 meters per second. The sampling frequency of the relative wind direction data is 10 Hz, and the accuracy of the relative wind direction data is better than 1 degree.

[0017] Further, the step S20 specifically includes: using a multi-scale wavelet decomposition method to process the ship speed data, selecting the Doppler 4th-order wavelet function as the decomposition basis function, obtaining the low-frequency component of the ship speed data as the speed stability component through 4-layer wavelet decomposition, using the high-frequency component of the ship speed data as the speed variation component, and determining the speed variation component according to the speed threshold of 0.5 meters per second; using a Fourier transform method to process the ship heading data, designing a low-pass filter with a cutoff frequency of 0.1 Hz, obtaining the low-frequency component of the ship heading data as the heading stability component through filtering, using the high-frequency component of the ship heading data as the heading variation component, and determining the heading variation component according to the heading threshold of 1 degree; using an empirical mode decomposition method to process the relative wind speed data, constructing upper and lower envelopes through cubic spline interpolation, calculating the mean value to obtain the relative wind speed data stability component, using the difference between the original data and the relative wind speed data stability component as the wind speed variation component, and determining the wind speed variation component according to the wind speed threshold of 0.3 meters per second.

[0018] Furthermore, the step S30 specifically includes: establishing a motion correlation function of the speed stability component, the heading stability component and the wind speed variation component based on fluid mechanics theory, the motion correlation function includes trigonometric function terms and linear terms, and calculating the trigonometric function term coefficients and the linear term coefficients by the least squares method; constructing a ship motion state matrix according to the motion correlation function, the ship motion state matrix is ​​a 3×3 matrix, the first row of the ship motion state matrix represents the contribution of speed to ship motion, the second row of the ship motion state matrix represents the contribution of heading to ship motion, and the third row of the ship motion state matrix represents the contribution of wind speed to ship motion, and the elements of the ship motion state matrix are obtained by discretizing the state space equation, and the discretization sampling period is 0.1 second; performing singular value decomposition on the ship motion state matrix, and eliminating the matrix singularity by setting a singular value threshold of 0.1.

[0019] Furthermore, the step S40 specifically includes: decomposing the ship speed data into a longitude velocity component and a latitude velocity component based on the vector decomposition principle, and calculating the longitude velocity component and the latitude velocity component by trigonometric functions; constructing a rotation matrix considering the influence of the ship heading data, the rotation matrix including a heading angle cosine term and a heading angle sine term; multiplying the longitude velocity component and the latitude velocity component by the rotation matrix to obtain a ship speed vector in a geographic coordinate system; converting the ship speed vector in the geographic coordinate system to a ship coordinate system by coordinate transformation, and calibrating the coordinate system conversion parameters by the least squares method.

[0020] Furthermore, the step S50 specifically includes: constructing a 2×2 environmental wind speed influence matrix; calculating the wind speed influence coefficient, the wind speed influence coefficient is related to the wind speed and the effective area, the wind speed influence coefficient is obtained by fitting the wind tunnel test data, and the wind speed influence coefficient ranges from 0.5 to 1.5; calculating the wind direction influence coefficient, the wind direction influence coefficient is related to the wind direction angle and the shape of the ship, the wind direction influence coefficient is obtained by a numerical simulation method, and the wind direction influence coefficient ranges from negative 1 to 1; combining the wind speed influence coefficient and the wind direction influence coefficient into the environmental wind speed influence matrix, the diagonal elements of the environmental wind speed influence matrix represent the main influence, and the non-diagonal elements of the environmental wind speed influence matrix represent the cross influence.

[0021] Furthermore, the step S60 specifically includes: converting the relative wind speed data and the relative wind direction data into a relative wind speed vector; multiplying the environmental wind speed influence matrix with the relative wind speed vector to obtain an environmental influence wind speed vector; multiplying the ship motion state matrix with the environmental influence wind speed vector to obtain a ship motion influence wind speed vector; synthesizing the ship speed vector with the ship motion influence wind speed vector to obtain an actual wind speed vector; and filtering the actual wind speed vector using a Kalman filter, wherein the Kalman filter process noise variance is 0.1, and the Kalman filter measurement noise variance is 0.05.

[0022] Further, the step S70 specifically includes: extracting the longitude component and the latitude component of the actual wind speed vector; calculating the angle between the actual wind speed vector and the true north direction by the inverse tangent function to obtain the initial true wind direction angle; constructing a 3×3 optimal path matrix, and optimizing the optimal path matrix elements by the dynamic programming method; iteratively optimizing the initial true wind direction angle based on the optimal path matrix, the optimization objective function is the mean square error between the measured value and the theoretical value, and the optimization termination condition is that the error is less than 0.1 degrees or the number of iterations exceeds 10 times; correcting the optimized wind direction angle by statistical analysis of historical data; the step S80 specifically includes: calculating the error between the actual wind speed vector and the reference wind speed vector The wind speed error compensation is obtained by calculating the difference between the true wind direction angle and the reference wind direction angle; the wind direction error compensation is obtained by calculating the error between the true wind direction angle and the reference wind direction angle; a wind speed compensator and a wind direction compensator are designed, and the parameters of the wind speed compensator and the wind direction compensator are calibrated by the least square method, wherein the wind speed compensator coefficient has a value range of 0.1 to 0.5, and the wind direction compensator coefficient has a value range of 0.2 to 0.8; the wind speed error compensation is applied to the actual wind speed vector to obtain corrected wind speed data; the wind direction error compensation is applied to the true wind direction angle to obtain corrected wind direction data; and the wind speed error compensation and the wind direction error compensation are limited according to a wind speed error compensation threshold of 0.3 meters per second and a wind direction error compensation threshold of 3 degrees.

[0023] A second aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores program instructions, and when the program instructions are run in a computer, they are used to execute the above-mentioned ship wind measurement method based on single Beidou positioning.

[0024] A third aspect of the present invention provides a ship wind measurement system based on single Beidou positioning, which includes the above-mentioned computer-readable storage medium.

[0025] The ship wind measurement method based on single Beidou positioning proposed in the present invention realizes high-precision measurement of the ship's motion state and environmental wind conditions by comprehensively utilizing the Beidou positioning system and ultrasonic wind speed and direction sensors. Compared with the prior art, this method has the following main technical effects: (1) Low measurement cost. The method of the present invention only requires a single Beidou positioning receiver and an ultrasonic wind speed and direction sensor. There is no need to install multiple positioning receivers or targeted external sensor devices, which greatly reduces the overall cost of the system. (2) High measurement accuracy. The method of the present invention utilizes the high-precision position and motion state data provided by the Beidou positioning system, and by establishing a coupling relationship model between the ship's motion state and the ambient wind speed, it can accurately calculate the actual ambient wind conditions, thus overcoming the existing measurement errors based on relative wind speed and heading data. At the same time, the optimization algorithms such as Kalman filtering and dynamic programming are used to further improve the measurement accuracy of wind speed and wind direction; (3) Simple system structure. The method of the present invention does not require the installation of additional data acquisition equipment. It only uses a single Beidou positioning receiver and an ultrasonic wind speed and direction sensor. The system structure is simple and compact, and is easy to deploy and integrate on a ship. Compared with existing wind measurement methods that require multiple sensors and complex circuits, the system of the present invention has better reliability and maintainability.

[0026] In summary, the ship wind measurement method based on single Beidou positioning proposed in the present invention solves the problems of high cost, limited accuracy, high system complexity, etc. existing in the existing wind measurement technology by innovatively establishing a coupling relationship model between the ship's motion state and the ambient wind speed and adopting advanced data processing algorithms, and provides a more economical, efficient and reliable technical solution for ship meteorological monitoring and navigation control. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of a ship wind measurement method based on single Beidou positioning. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0029] like Figure 1 As shown, it is a flow chart of a ship wind measurement method based on single Beidou positioning provided by the first aspect of the present invention. In this embodiment, the following steps are included: The specific implementation method of each step is described in detail below: The specific implementation method of step S10 is based on the data acquisition principle of the high-precision positioning function of the Beidou positioning system and the ultrasonic wind speed and direction sensor. First, the Beidou positioning chip is used to receive the Beidou navigation satellite signal, and the real-time longitude and latitude data of the ship are obtained through differential correction processing. The sampling frequency of the real-time position data of the ship is 1 Hz. The collected data includes longitude data and latitude data, wherein the accuracy of the longitude data is better than 0.000001 degrees, and the accuracy of the latitude data is better than 0.000001 degrees; then the speed measurement module of the Beidou positioning system is used to calculate the ship's speed data, and the speed data is obtained through speed factor calibration correction. The sampling frequency of speed data is 1 Hz, and the accuracy is better than 0.1 meters per second. At the same time, the heading measurement module of the Beidou positioning system is used to calculate the ship heading data, and the heading data is obtained through heading deviation calibration. The sampling frequency of heading data is 1 Hz, and the accuracy is better than 0.1 degrees. Secondly, based on the principle of ultrasonic time difference method, a dual-axis ultrasonic wind speed and direction sensor is used to construct an anemometer. The relative wind speed and wind direction data are calculated by measuring the ultrasonic propagation time difference between different sensors. The sampling frequency of relative wind speed data is 10 Hz, and the accuracy is better than 0.1 meters per second. The sampling frequency of relative wind direction data is 10 Hz, and the accuracy is better than 1 degree.

[0030] The specific implementation method of step S20 is to first decompose the speed data of the ship into components, and based on the wavelet analysis theory, use the multi-scale wavelet decomposition method to process the speed data, select the Doppler 4th-order wavelet function as the decomposition basis function, and obtain the low-frequency component of the speed as the speed stability component through four-layer wavelet decomposition, and use the high-frequency component as the speed variation component, wherein the threshold of the speed data is selected as 0.5 meters per second, and when the speed change exceeds the threshold, it is determined as a variation component; then decompose the heading data of the ship into components, and use the Fourier transform method to first convert the heading data into the frequency domain, and design the cutoff A low-pass filter with a stop frequency of 0.1 Hz is used. The low-frequency component of the heading is obtained by filtering as the heading stable component, and the high-frequency component is taken as the heading changing component. The threshold of the heading data is selected as 1 degree. When the heading change exceeds the threshold, it is determined to be a changing component. Finally, the relative wind speed data is decomposed into components. Based on the empirical mode decomposition theory, the upper and lower envelopes are constructed by cubic spline interpolation. The mean value is calculated to obtain the stable component of the wind speed. The difference between the original data and the stable component is taken as the wind speed changing component. The threshold of the wind speed data is selected as 0.3 meters per second. When the wind speed change exceeds the threshold, it is determined to be a changing component.

[0031] The specific implementation method of step S30 is to first establish a motion correlation function between the stable component of ship speed, the stable component of heading and the variable component of wind speed based on the theory of fluid mechanics, and the correlation function includes trigonometric function terms and linear terms, wherein the trigonometric function terms reflect the periodic influence of the heading angle on the wind speed, and the linear terms represent the direct relationship between the speed and the wind speed, and the coefficients of each term are calculated by the least squares method; then, a ship motion state matrix is ​​constructed according to the motion correlation function, and the matrix is ​​a 3×3 matrix, the first row of the matrix represents the contribution of the speed to the ship motion, the second row represents the contribution of the heading to the ship motion, and the third row represents the contribution of the wind speed to the ship motion, and each element of the matrix is ​​obtained by discretization of the state space equation, and the discretization sampling period is 0.1 seconds; finally, the ship motion state matrix is ​​subjected to singular value decomposition, and the singularity in the matrix is ​​eliminated by setting the singular value threshold to 0.1, thereby improving the stability of the matrix.

[0032] The specific implementation method of step S40 is to first decompose the ship speed into speed components in the longitude and latitude directions based on the principle of vector decomposition, and calculate the component values ​​in the two directions through trigonometric functions; then consider the influence of the ship's heading angle and construct a rotation matrix, which contains the cosine and sine terms of the heading angle; then multiply the speed component with the rotation matrix to obtain the ship's speed vector in the geographic coordinate system; finally, transform the speed vector from the geographic coordinate system to the ship coordinate system through coordinate transformation, and the transformation matrix is ​​constructed based on the angle between the two coordinate systems, and the coordinate system transformation parameters are calibrated by the least squares method.

[0033] The specific implementation method of step S50 is to first consider the influence of wind speed and wind direction on ship movement based on wind field analysis theory, and construct an environmental wind speed influence matrix, which is a 2×2 matrix; then calculate the wind speed influence coefficient, which is related to the wind speed and the effective area, and is obtained by fitting the wind tunnel test data, and the wind speed coefficient ranges from 0.5 to 1.5; then calculate the wind direction influence coefficient, which is related to the wind direction angle and the shape of the ship, and is obtained by numerical simulation method, and the wind direction coefficient ranges from negative 1 to 1; finally, combine the wind speed influence coefficient and the wind direction influence coefficient into a matrix form, the diagonal elements of the matrix represent the main influence, and the non-diagonal elements represent the cross influence.

[0034] The specific implementation method of step S60 is to first convert the relative wind speed data into a vector form, including wind speed magnitude and wind direction angle information; then multiply the environmental wind speed influence matrix with the relative wind speed vector to obtain the wind speed vector after considering the environmental influence; then multiply the ship motion state matrix with the wind speed vector after the environmental influence to obtain the wind speed vector considering the influence of ship motion; then synthesize the ship speed vector and the wind speed vector to obtain the actual wind speed vector; finally, filter the actual wind speed vector through a Kalman filter, and the process noise variance of the filter is 0.1, and the measurement noise variance is 0.05.

[0035] The specific implementation method of step S70 is to first extract the longitude component and the latitude component of the actual wind speed vector; then calculate the angle between the wind speed vector and the true north direction through the inverse tangent function to obtain the initial true wind direction angle; then construct an optimal path matrix, which is a 3×3 matrix, and the matrix elements are optimized by a dynamic programming method; then iteratively optimize the initial wind direction angle based on the optimal path matrix, and the optimization objective function is the mean square error between the measured value and the theoretical value, and the termination condition of the iteration is that the error is less than 0.1 degrees or the number of iterations exceeds 10 times; finally, the optimized wind direction angle is corrected, and the correction term is obtained by statistical analysis of historical data.

[0036] The specific implementation method of step S80 is to first calculate the error between the actual wind speed vector and the reference wind speed vector based on feedback control theory to obtain the wind speed error compensation; then calculate the error between the real wind direction angle and the reference wind direction angle to obtain the wind direction error compensation; then design the wind speed compensator and the wind direction compensator, and the parameters of the compensator are calibrated by the least squares method, the wind speed compensation coefficient ranges from 0.1 to 0.5, and the wind direction compensation coefficient ranges from 0.2 to 0.8; then apply the wind speed error compensation to the actual wind speed vector to obtain corrected wind speed data; finally, apply the wind direction error compensation to the real wind direction angle to obtain corrected wind direction data; wherein the threshold value of the wind speed error compensation is 0.3 meters per second, and the threshold value of the wind direction error compensation is 3 degrees, and when the compensation exceeds the threshold value, the threshold value is used for limiting processing.

[0037] The above steps realize the ship wind measurement method based on single Beidou positioning through the comprehensive application of multiple algorithms and theories. The main methods used are wavelet analysis, Fourier transform, empirical mode decomposition, least squares method, state space theory, vector decomposition, coordinate transformation, wind field analysis, Kalman filtering, dynamic programming and feedback control. There are strict logical relationships and data transmission relationships between each step, forming a complete wind measurement system.

[0038] The calculation process or equation involved in the present invention is described in detail below: Data collection in step S10: The real-time position data vector of the ship is expressed as follows: ; In the formula, is the longitude at time t; is the latitude at time t; is the ship speed at time t; is the heading angle at time t.

[0039] The real-time data vector of the anemometer is represented as follows: ; In the formula, is the relative wind speed at time t; is the relative wind direction angle at time t.

[0040] Component decomposition in step S20: Speed ​​decomposition formula: ; In the formula, is the speed stabilizing component; is the speed variation component; is the speed error term, ranging from -0.5 to 0.5 m / s.

[0041] Heading decomposition formula: ; In the formula, is the heading stability component; is the heading change component; is the heading error term, ranging from -1° to 1°.

[0042] Relative wind speed decomposition formula: ; In the formula, is the stable component of wind speed; is the wind speed variation component; is the wind speed error term, ranging from -0.3 to 0.3 m / s.

[0043] Motion correlation function in step S30: ; In the formula, is the coefficient to be determined; is the correlation function error term, ranging from -0.1 to 0.1.

[0044] Ship motion state matrix: ; In the formula, is the ship motion state coefficient.

[0045] Velocity vector calculation in step S40: Ship velocity vector in geographic coordinate system: ; In the formula, is the velocity component in the longitude direction; is the velocity component in the latitudinal direction; is the ship heading angle; is the velocity error vector.

[0046] Coordinate transformation matrix: ; In the formula, is the coordinate system transformation angle.

[0047] Ambient wind speed impact matrix in step S50: ; In the formula, is the wind speed influence coefficient.

[0048] The actual wind speed vector calculation in step S60: ; In the formula, is the actual wind speed vector; is the ship velocity vector; is the synthetic error vector.

[0049] Calculation of the true wind direction angle in step S70: ; In the formula, are the x and y components of the actual wind speed vector respectively; is the angle correction term.

[0050] Optimal path matrix: ; In the formula, is the path optimization coefficient.

[0051] Error compensation in step S80: Wind speed error compensation: ; In the formula, is the wind speed compensation coefficient; is the reference wind speed vector; To compensate for the error.

[0052] Wind direction error compensation: ; In the formula, is the wind direction compensation coefficient; is the reference wind direction angle; To compensate for the error.

[0053] Corrected wind speed and direction: ; .

[0054] The construction principles and meanings of these equations are as follows: 1. The position data vector is in the form of a four-dimensional vector, which contains the complete state information of the ship's motion; 2. The component decomposition uses an additive model to separate the stable component from the variable component for easy subsequent analysis; 3. The motion correlation function adopts the form of trigonometric function, taking into account the periodic characteristics of the heading angle; 4. The state matrix and influence matrix adopt 3×3 and 2×2 forms, which can express multi-dimensional interaction relationships; 5. The coordinate transformation matrix adopts the form of rotation matrix, which ensures the orthogonality of coordinate transformation; 6. The introduction of error terms takes into account the impact of measurement error and systematic error; 7. The optimal path matrix is ​​used to optimize the angle calculation process and improve accuracy; 8. The calculation of compensation amount adopts the proportional-error model, which has good adaptability.

[0055] The derivation process of each equation is explained in detail below.

[0056] 1. Ship real-time position data vector Derivation of: The vector is constructed based on the basic output data of the Beidou positioning system. The steps are as follows: Step 1: Get NMEA-0183 protocol data from the Beidou positioning system; Step 2: Parse the NMEA data Statement to extract latitude, longitude, speed and heading information; Step 3: Integrate the scattered data into vector form: ; The position accuracy can reach meter level, the speed accuracy is 0.1m / s, and the heading accuracy is 0.1°.

[0057] 2. Anemometer real-time data vector Derivation of: The vector is constructed based on the output data of the ultrasonic anemometer. The steps are as follows: Step 1: Collect the RS485 output data of the anemometer; Step 2: Data preprocessing, including denoising and outlier removal; Preprocessing formula: ; ; In the formula, is the sampling interval, usually 0.1s; is the median filter operation. Step 3: Construct the anemometer data vector: .

[0058] 3. Derivation of speed decomposition formula: Based on the time series analysis theory, the wavelet decomposition method is adopted, and the steps are as follows: Step 1: Perform wavelet transform on the original speed sequence: ; In the formula, As the wavelet basis function, db4 wavelet is selected. Step 2: Extract the low-frequency part as the stable component: ; In the formula, The empirical value for the number of decomposition layers is 3-5. Step 3: Calculate the variable component: ; Finally, the decomposition formula is obtained: .

[0059] 4. Derivation of heading decomposition formula: Using the Fourier analysis method, the steps are as follows: Step 1: Perform Fourier transform: ; Step 2: Design a low-pass filter: ; In the formula, The cut-off frequency is 0.1 Hz. Step 3: Extract the stable component: ; Step 4: Calculate the variable component: ; Finally get: .

[0060] 5. Derivation of relative wind speed decomposition formula: The empirical mode decomposition (EMD) method is used, and the steps are as follows: Step 1: Identify extreme points; Step 2: Construct envelope: and Use cubic spline interpolation; Step 3: Calculate the mean: ; Step 4: Extract the intrinsic mode function (IMF), and the first IMF is used as the variable component ; Step 5: The remaining part is used as a stable component ; Finally get: .

[0061] 6. Derivation of motion correlation function: Based on the theory of fluid mechanics, considering the ship-wind field coupling effect, the steps are as follows: Step 1: Establish the wind pressure equation: ; In the formula, is the air density; is the wind pressure coefficient; is the reference area. Step 2: Consider the impact of ship motion: ;in, Related to ship speed and heading. Step 3: Linearization processing to obtain: .

[0062] 7. Construction of ship motion state matrix: Based on the state space theory, the steps are as follows: Step 1: Define the state variables: ; Step 2: Establish the state transfer equation: ; Step 3: Discretization processing to obtain: ; In the formula, is the sampling period.

[0063] 8. Derivation of velocity vector calculation: Based on the principle of vector decomposition, the steps are as follows: Step 1: Establish the velocity component of the geographic coordinate system: ; ; Step 2: Introduce the error term and get: .

[0064] 9. Construction of environmental wind speed impact matrix: Based on wind field analysis theory, the steps are as follows: Step 1: Establish a wind speed impact model: ; ; ; ; In the formula, is the wind speed influence coefficient; is the wind direction correction angle. Step 2: Combine into a matrix form: .

[0065] 10. Derivation of actual wind speed vector calculation: Based on the principle of vector synthesis, the steps are as follows: Step 1: Calculate the relative wind speed vector: ; Step 2: Consider environmental impact: ; Step 3: Consider ship motion: .

[0066] 11. Derivation of the calculation of the true wind direction angle: Using the optimal estimation theory, the steps are as follows: Step 1: Calculate the initial wind direction angle: ; Step 2: Construct optimization objective function: ; Step 3: Iterative optimization through the optimal path matrix: ; Finally get: .

[0067] 12. Derivation of error compensation amount: Based on feedback control theory, the steps are as follows: Step 1: Establish an error model: ; ; Step 2: Design the compensator: ; ; In the formula, Calibrated by least squares method.

[0068] The effects of these equations are: 1. The decomposition algorithm can effectively separate stable and variable components, improving the accuracy of data processing; 2. The motion correlation function takes into account the nonlinear effect and improves the adaptability of the model; 3. Matrix operations improve computational efficiency and facilitate real-time processing; 4. The error compensation mechanism improves the measurement accuracy, and the overall accuracy of the system can reach: wind speed error <0.3m / s, wind direction error <3°.

[0069] A second aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores program instructions, and when the program instructions are run in a computer, they are used to execute the above-mentioned ship wind measurement method based on single Beidou positioning.

[0070] A third aspect of the present invention provides a ship wind measurement system based on single Beidou positioning, which includes the above-mentioned computer-readable storage medium.

[0071] The wind measurement method of the present invention can solve the problems existing in the prior art mainly due to the following innovations: 1. Use a single Beidou positioning system to obtain high-precision ship motion state data. Different from the existing method based on multiple positioning receivers, the present invention only uses a single Beidou positioning receiver to obtain high-precision motion state data such as the ship's longitude and latitude, speed, and heading through technical means such as differential correction. This not only reduces the system cost, but also avoids the influence of the relative position changes between multiple positioning receivers on the measurement accuracy.

[0072] 2. Establish a coupled relationship model between the ship's motion state and the ambient wind speed. The method of the present invention establishes a motion correlation function containing trigonometric functions and linear terms by analyzing the physical relationship between the ship's speed, heading and relative wind speed. The correlation function is converted into a ship motion state matrix and an ambient wind speed influence matrix, and a state space model of the coupling of the two is established. This lays the foundation for the subsequent calculation of the actual wind speed vector.

[0073] 3. Use optimization algorithms to improve measurement accuracy. When calculating the actual wind speed vector and the true wind direction angle, the method of the present invention uses algorithms such as Kalman filtering and dynamic programming. Kalman filtering can effectively eliminate random noise in the measurement process and improve the accuracy of the wind speed vector; dynamic programming can find the optimal solution for the true wind direction angle through multiple iterations of optimization, thereby improving the accuracy of wind direction measurement.

[0074] 4. Introduce error compensation mechanism. In order to further eliminate various error sources in the system, the present invention adopts an error compensation method based on feedback control theory when finally calculating the corrected wind speed and wind direction. By analyzing the deviation between the actual measured value and the reference value and dynamically adjusting the compensation amount, the system error caused by measurement error, modeling error, etc. can be effectively suppressed.

[0075] A specific embodiment 1 of the present invention is provided below. The specific method of each step in this embodiment 1 is described in detail as follows: The specific implementation method of step S10 is based on the data acquisition principle of the high-precision positioning function of the Beidou positioning system and the ultrasonic wind speed and direction sensor. First, the Beidou positioning chip is used to receive the Beidou navigation satellite signal, and the real-time longitude and latitude data of the ship are obtained through differential correction processing. The sampling frequency of the real-time position data of the ship is 1 Hz, and the collected data includes longitude data and latitude data, wherein the accuracy of the longitude data is better than 0.000001 degrees, and the accuracy of the latitude data is better than 0.000001 degrees. Then the speed measurement module of the Beidou positioning system is used to calculate the ship's speed data, and the speed data is obtained by speed factor calibration correction. The sampling frequency of the speed data is 1 Hz, and the accuracy is better than 0.1 meters per second. At the same time, the heading measurement module of the Beidou positioning system is used to calculate the ship's heading data, and the heading data is obtained through heading deviation calibration. The sampling frequency of the heading data is 1 Hz, and the accuracy is better than 0.1 degrees. Secondly, based on the principle of ultrasonic time difference method, a dual-axis ultrasonic wind speed and direction sensor is used to build an anemometer. The relative wind speed and wind direction data are calculated by measuring the ultrasonic propagation time difference between different sensors. The sampling frequency of relative wind speed data is 10 Hz, and the accuracy is better than 0.1 meters per second. The sampling frequency of relative wind direction data is 10 Hz, and the accuracy is better than 1 degree.

[0076] The specific implementation method of step S20 is to first decompose the speed data of the ship into components. Based on the wavelet analysis theory, a multi-scale wavelet decomposition method is used to process the speed data, and the Doppler 4th-order wavelet function is selected as the decomposition basis function. The low-frequency component of the speed is obtained as the speed stability component through four-layer wavelet decomposition, and the high-frequency component is used as the speed change component. The threshold of the speed data is selected as 0.5 meters per second, and when the speed changes beyond the threshold, it is determined as a change component. Then the heading data of the ship is decomposed into components, and the Fourier transform method is used to first convert the heading data into the frequency domain, and a low-pass filter with a cutoff frequency of 0.1 Hz is designed. The low-frequency component of the heading is obtained as the heading stability component through filtering, and the high-frequency component is used as the heading change component. The threshold of the heading data is selected as 1 degree, and when the heading changes beyond the threshold, it is determined as a change component. Finally, the relative wind speed data is decomposed into components. Based on the empirical mode decomposition theory, the upper and lower envelopes are constructed by cubic spline interpolation. The mean value is calculated to obtain the stable component of the wind speed, and the difference between the original data and the stable component is used as the variable component of the wind speed. The threshold of the wind speed data is selected as 0.3 meters per second. When the wind speed changes beyond the threshold, it is determined as a variable component.

[0077] The specific implementation method of step S30 is to first establish a motion correlation function between the stable component of ship speed, the stable component of heading and the variable component of wind speed based on the theory of fluid mechanics. The correlation function contains trigonometric terms and linear terms, wherein the trigonometric terms reflect the periodic influence of the heading angle on the wind speed, and the linear terms represent the direct relationship between the speed and the wind speed. The coefficients of each item are calculated by the least squares method. Then, the ship motion state matrix is ​​constructed according to the motion correlation function. The matrix is ​​a 3×3 matrix. The first row of the matrix represents the contribution of the speed to the ship motion, the second row represents the contribution of the heading to the ship motion, and the third row represents the contribution of the wind speed to the ship motion. Each element of the matrix is ​​obtained by discretization of the state space equation, and the discretization sampling period is 0.1 seconds. Finally, the ship motion state matrix is ​​subjected to singular value decomposition, and the singularity in the matrix is ​​eliminated by setting the singular value threshold to 0.1, thereby improving the stability of the matrix.

[0078] The specific implementation method of step S40 is to first decompose the ship's speed into speed components in the longitude and latitude directions based on the vector decomposition principle, and calculate the component values ​​in the two directions through trigonometric functions. Then, considering the influence of the ship's heading angle, a rotation matrix is ​​constructed, which contains the cosine and sine terms of the heading angle. Then, the speed component is multiplied by the rotation matrix to obtain the ship's speed vector in the geographic coordinate system. Finally, the speed vector is converted from the geographic coordinate system to the ship coordinate system through coordinate transformation. The construction of the transformation matrix is ​​based on the angle between the two coordinate systems, and the coordinate system conversion parameters are calibrated by the least squares method.

[0079] The specific implementation method of step S50 is to first consider the influence of wind speed and wind direction on the movement of the ship based on the wind field analysis theory, and construct an environmental wind speed influence matrix, which is a 2×2 matrix. Then calculate the wind speed influence coefficient, which is related to the wind speed and the effective area, and is obtained by fitting the wind tunnel test data. The value range of the wind speed coefficient is 0.5 to 1.5. Then calculate the wind direction influence coefficient, which is related to the wind direction angle and the shape of the ship, and is obtained by numerical simulation method. The value range of the wind direction coefficient is negative 1 to 1. Finally, the wind speed influence coefficient and the wind direction influence coefficient are combined into a matrix form, and the diagonal elements of the matrix represent the main influence, and the non-diagonal elements represent the cross influence.

[0080] The specific implementation of step S60 is to first convert the relative wind speed data into a vector form, including wind speed magnitude and wind direction angle information. Then the environmental wind speed influence matrix is ​​multiplied by the relative wind speed vector to obtain the wind speed vector after considering the environmental influence. Then the ship motion state matrix is ​​multiplied by the wind speed vector after the environmental influence to obtain the wind speed vector considering the influence of the ship motion. Then the ship speed vector is synthesized with the wind speed vector to obtain the actual wind speed vector. Finally, the actual wind speed vector is filtered by a Kalman filter, and the process noise variance of the filter is 0.1 and the measurement noise variance is 0.05.

[0081] The specific implementation method of step S70 is to first extract the longitude component and the latitude component of the actual wind speed vector. Then, the angle between the wind speed vector and the true north direction is calculated by the inverse tangent function to obtain the initial true wind direction angle. Then, the optimal path matrix is ​​constructed, which is a 3×3 matrix, and the matrix elements are optimized by the dynamic programming method. Then, the initial wind direction angle is iteratively optimized based on the optimal path matrix. The objective function of the optimization is the mean square error between the measured value and the theoretical value. The termination condition of the iteration is that the error is less than 0.1 degrees or the number of iterations exceeds 10 times. Finally, the optimized wind direction angle is corrected, and the correction term is obtained by statistical analysis of historical data.

[0082] The specific implementation method of step S80 is to first calculate the error between the actual wind speed vector and the reference wind speed vector based on the feedback control theory to obtain the wind speed error compensation. Then calculate the error between the true wind direction angle and the reference wind direction angle to obtain the wind direction error compensation. Then design the wind speed compensator and the wind direction compensator. The parameters of the compensator are calibrated by the least squares method. The value range of the wind speed compensation coefficient is 0.1 to 0.5, and the value range of the wind direction compensation coefficient is 0.2 to 0.8. Then apply the wind speed error compensation to the actual wind speed vector to obtain the corrected wind speed data. Finally, apply the wind direction error compensation to the true wind direction angle to obtain the corrected wind direction data. The threshold of the wind speed error compensation is 0.3 meters per second, and the threshold of the wind direction error compensation is 3 degrees. When the compensation exceeds the threshold, the threshold is used for limiting processing.

[0083] A specific embodiment 2 of the present invention is provided below. The specific method of each step in this embodiment 2 is described in detail as follows: The specific implementation of step S10 is based on the data collection principle of the high-precision positioning function of the Beidou positioning system and the ultrasonic wind speed and direction sensor. First, the Beidou positioning chip is used to receive the Beidou navigation satellite signal, and the real-time longitude and latitude data of the ship is obtained through differential correction processing. The sampling frequency of the ship's real-time position data is 1 Hz, and the collected data includes longitude data and latitude data, among which the accuracy of longitude data is better than The accuracy of latitude and longitude data is better than Degrees. Among them, the real-time position data vector of the ship is expressed as follows: ; In the formula, for The longitude of the moment, for The latitude of the moment, for The speed of the moment, for The heading angle at the moment.

[0084] Then, the speed measurement module of the Beidou positioning system is used to calculate the ship speed data, and the speed data is obtained through speed factor calibration correction. The speed data sampling frequency is 1 Hz, and the accuracy is better than Meters per second. At the same time, the heading measurement module of the Beidou positioning system is used to calculate the ship's heading data, and the heading data is obtained through heading deviation calibration. The heading data sampling frequency is 1 Hz, and the accuracy is better than Spend.

[0085] Secondly, based on the principle of ultrasonic time difference method, a dual-axis ultrasonic wind speed and direction sensor is used to build an anemometer. The relative wind speed and wind direction data are calculated by measuring the ultrasonic propagation time difference between different sensors. The relative wind speed data sampling frequency is 10 Hz, and the accuracy is better than Meters per second, the relative wind direction data sampling frequency is 10 Hz, the accuracy is better than Degrees. The relative wind speed and wind direction data vector is expressed as follows: ; In the formula, for The relative wind speed at the time, for The relative wind direction angle at the moment.

[0086] The purpose of the above data collection is to obtain complete status information of ship motion and environmental wind conditions, and to provide basic data support for subsequent component decomposition, state modeling and wind speed solution.

[0087] The specific implementation method of step S20 is to perform component decomposition on the ship's speed data, heading data and relative wind speed data.

[0088] First, the speed data is decomposed into components. Based on wavelet analysis theory, the multi-scale wavelet decomposition method is used to process the speed data. The fourth-order Doppler wavelet function is selected as the decomposition basis function, and the low-frequency component of the speed is obtained as the stable component of the speed through four-layer wavelet decomposition. , taking the high frequency component as the speed variation component The speed decomposition formula is as follows: ; In the formula, is the speed error term, and its value range is Meters per second. When the speed changes by more than Meters per second, it is determined as a variable component.

[0089] Then, the heading data is decomposed into components. Using the Fourier transform method, the heading data is first converted to the frequency domain, and the cutoff frequency is designed to be A Hertz low-pass filter is used to obtain the low-frequency component of the heading as the heading stability component. , taking the high frequency component as the heading change component The heading decomposition formula is as follows: ; In the formula, is the heading error term, and its value range is When the heading change exceeds , it is determined to be a variable component.

[0090] Finally, the relative wind speed data is decomposed into components. Based on the empirical mode decomposition theory, the upper and lower envelopes are constructed by cubic spline interpolation, and the mean value is calculated to obtain the stable component of the wind speed. , the difference between the original data and the stable component is taken as the wind speed variation component The relative wind speed decomposition formula is as follows: ; In the formula, is the wind speed error term, and its value range is Meters per second. When the wind speed changes by more than Meters per second, it is determined as a variable component.

[0091] The purpose of the above component decomposition is to separate the stable component and the variable component to provide good input data for subsequent state modeling and wind speed solution.

[0092] The specific implementation method of step S30 is to establish a motion correlation function between the ship's speed stability component, the heading stability component and the wind speed variation component, and construct a ship motion state matrix based on the correlation function.

[0093] First, based on the theory of fluid mechanics, the following motion correlation function is established: ; In the formula, , and is the coefficient to be determined, is the correlation function error term, and its value range is The correlation function contains trigonometric terms and linear terms. The trigonometric terms reflect the periodic effect of the heading angle on the wind speed, and the linear terms represent the direct relationship between the ship speed and the wind speed. The coefficients are calculated by the least squares method.

[0094] Then, the ship motion state matrix is ​​constructed according to the above motion correlation function : ; In the formula, is the ship motion state coefficient. The first row of the matrix represents the contribution of speed to ship motion, the second row represents the contribution of heading to ship motion, and the third row represents the contribution of wind speed to ship motion. The matrix elements are obtained by discretizing the state space equation, and the discretization sampling period is Second.

[0095] Finally, the singular value decomposition of the ship motion state matrix is ​​performed, and the singular value threshold is set as , eliminate the singularity in the matrix and improve the stability of the matrix.

[0096] The purpose of the above steps is to establish a coupling relationship model between ship motion and ambient wind speed, which provides a basis for the subsequent calculation of ship velocity vector and actual wind speed vector.

[0097] The specific implementation of step S40 is to calculate the ship velocity vector according to the ship motion state matrix and convert it from the geographic coordinate system to the ship coordinate system.

[0098] First, based on the principle of vector decomposition, the ship speed is decomposed into speed components in the longitude and latitude directions, and the component values ​​in the two directions are calculated by the following trigonometric functions: ; In the formula, is the velocity component in the longitude direction, is the velocity component in the latitudinal direction, is the ship heading angle, is the velocity error vector.

[0099] Then, considering the influence of the ship's heading angle, the following rotation matrix is ​​constructed: ; In the formula, is the coordinate system transformation angle.

[0100] Next, multiply the velocity component by the rotation matrix to obtain the ship velocity vector in the geographic coordinate system .

[0101] Finally, the velocity vector is transformed from the geographic coordinate system to the ship coordinate system through coordinate transformation. The transformation matrix is ​​constructed based on the angle between the two coordinate systems, and the coordinate system transformation parameters are calibrated by the least squares method.

[0102] The purpose of the above steps is to convert the ship motion state data into a velocity vector representation in the ship coordinate system, providing a basis for the subsequent synthesis with the ambient wind speed.

[0103] The specific implementation of step S50 is to construct an environmental wind speed influence matrix to represent the influence of wind speed and wind direction on the motion of the ship.

[0104] First, based on the wind field analysis theory, considering the influence of wind speed and wind direction on ship motion, the following environmental wind speed influence matrix is ​​constructed: : ; In the formula, is the wind speed influence coefficient.

[0105] Then, calculate the wind speed influence coefficient and The wind speed influence coefficient is related to the wind speed and the area of ​​action. It is obtained by fitting the wind tunnel test data and has a value range of .

[0106] Next, calculate the wind direction influence coefficient and The wind direction influence coefficient is related to the wind direction angle and the ship shape and is obtained through numerical simulation method. The value range is .

[0107] Finally, the wind speed influence coefficient and wind direction influence coefficient are combined into a matrix form, where the diagonal elements of the matrix represent the main influences and the off-diagonal elements represent the cross-influences.

[0108] The purpose of the above steps is to establish a model of the impact of ambient wind speed on ship motion, providing a basis for the subsequent calculation of the actual wind speed vector.

[0109] The specific implementation of step S60 is to calculate the actual wind speed vector according to the ship motion state matrix and the environmental wind speed influence matrix.

[0110] First, the relative wind speed data is converted into a vector form, which contains wind speed magnitude and wind direction angle information.

[0111] Then, the environmental wind speed influence matrix Multiply it with the relative wind speed vector to get the wind speed vector after considering the environmental impact .

[0112] Next, the ship motion state matrix Multiply it by the wind speed vector after environmental influence to get the wind speed vector considering the influence of ship motion. .

[0113] Then, the ship velocity vector Combined with the above wind speed vector, the actual wind speed vector is obtained : ; In the formula, is the synthetic error vector.

[0114] Finally, the actual wind speed vector is filtered by the Kalman filter, and the process noise variance of the filter is , the measurement noise variance is .

[0115] The purpose of the above steps is to comprehensively consider the influence of ship motion and ambient wind speed, calculate the actual wind speed vector, and provide a basis for the subsequent calculation of the true wind direction angle.

[0116] The specific implementation of step S70 is to calculate the true wind direction angle according to the actual wind speed vector and optimize it through the optimal path matrix.

[0117] First, extract the actual wind speed vector The longitude component of and the latitude component .

[0118] Then, the angle between the wind speed vector and the true north direction is calculated by the inverse tangent function , get the initial true wind direction angle: ; In the formula, is the angle correction term.

[0119] Next, construct the following optimal path matrix : ; In the formula, is the path optimization coefficient.

[0120] Then, based on the optimal path matrix, the initial wind direction angle Iterative optimization is performed, and the optimization objective function is the mean square error between the measured value and the theoretical value. The termination condition of the iteration is that the error is less than or the number of iterations exceeds Second-rate.

[0121] Finally, the optimized wind direction angle is corrected, and the correction term is obtained through statistical analysis of historical data.

[0122] The purpose of the above steps is to improve the measurement accuracy of the true wind direction angle through the optimization algorithm, providing a basis for the subsequent error compensation of wind speed and wind direction.

[0123] The specific implementation method of step S80 is to calculate the wind speed error compensation amount and the wind direction error compensation amount according to the ship motion state matrix and the environmental wind speed influence matrix, and apply them to the actual wind speed vector and the true wind direction angle to obtain the corrected wind speed data and wind direction data.

[0124] First, based on feedback control theory, the actual wind speed vector is calculated With reference wind speed vector The error between the wind speed error compensation : ; In the formula, is the wind speed compensation coefficient, and its value range is , To compensate for the error.

[0125] Then, calculate the true wind direction angle With reference wind direction angle The error between the wind direction error and the wind direction error compensation is obtained. : ; In the formula, is the wind direction compensation coefficient, and its value range is , To compensate for the error.

[0126] Next, the wind speed error compensation is applied to the actual wind speed vector , get the corrected wind speed data : ; Finally, the wind direction error compensation is applied to the true wind direction angle , get the corrected wind direction data : ; Among them, when the wind speed error compensation exceeds Meters per second, or the wind direction error compensation exceeds When , the threshold is used for limiting processing.

[0127] The purpose of the above steps is to eliminate the systematic error and random error in the measurement process through the error compensation method, improve the measurement accuracy of wind speed and wind direction, and meet the needs of subsequent ship navigation control and meteorological monitoring.

[0128] In order to better understand and implement the present invention, the following provides Example 3 of a specific application scenario of the present invention: A marine engineering company deployed a fleet of ships near an oil field in the South China Sea to perform offshore drilling and platform construction tasks. In order to ensure operational safety and improve operational efficiency, the company urgently needed a wind measurement system that could accurately monitor the environmental wind conditions in the operating area.

[0129] After investigation, the technical department of the enterprise found that the existing ship wind measurement technology has problems such as high cost, limited accuracy, and high system complexity. Therefore, they decided to adopt the ship wind measurement method based on single Beidou positioning proposed in this invention to design and deploy a wind measurement monitoring system. The specific implementation process is as follows: First, the company selected a workboat as the carrier of the wind measurement system. A set of wind measurement equipment consisting of a Beidou positioning receiver and an ultrasonic wind speed and direction sensor was installed on the top of the mast of the ship. The Beidou positioning receiver model is the BDS4000 series, which has millimeter-level positioning accuracy and an update frequency of 1 Hz, and can provide high-precision real-time position, speed and heading data of the ship. The ultrasonic wind speed and direction sensor adopts a dual-axis design. By measuring the ultrasonic propagation time difference between different sensors, it can collect relative wind speed and relative wind direction data at a frequency of 10 Hz, with measurement accuracy better than 0.1 m / s and 1 degree respectively.

[0130] After the wind measurement equipment was installed, the company's technical staff debugged and calibrated the entire wind measurement system. First, the performance of the ultrasonic wind speed and direction sensor was calibrated and error corrected using professional wind tunnel test equipment. By comparing the test with the standard wind speed and direction instrument, the measurement error range of the sensor under different wind speed and wind direction conditions was determined. At the same time, the position, speed and heading data of the Beidou positioning receiver were calibrated and corrected to eliminate the influence of installation errors and environmental factors.

[0131] Next, the technicians wrote the relevant data processing algorithm program according to the specific implementation of the present invention. It mainly includes: 1. Component decomposition of the ship's real-time position data, speed data and heading data, and extraction of stable components and variable components. Taking speed data as an example, the speed data is decomposed into low-frequency stable components through wavelet analysis method. and high frequency variation components , where the threshold of speed data is selected as 0.5 m / s.

[0132] 2. Based on the theory of fluid mechanics, establish the motion correlation function between the ship's speed stability component, heading stability component and relative wind speed change component , and use the least squares method to calculate the coefficients , , , the error term of the correlation function exist within the range.

[0133] 3. According to the above motion correlation function, construct a 3×3 ship motion state matrix , matrix element It is obtained by discretizing the state space equation, and the discretization sampling period is 0.1 second. The matrix is ​​subjected to singular value decomposition, and the singular value threshold is set to 0.1 to eliminate the singularity in the matrix.

[0134] 4. Establish a 2×2 environmental wind speed impact matrix , wind speed influence coefficient The value range is 0.5~1.5, and the wind direction influence coefficient The value range is -1~1.

[0135] 5. According to the ship motion state matrix and the environmental wind speed influence matrix, the Kalman filter algorithm is used to calculate the actual wind speed vector , the process noise variance is 0.1, and the measurement noise variance is 0.05.

[0136] 6. Use dynamic programming algorithm to optimize the true wind direction angle , construct a 3×3 optimal path matrix ,The optimal solution is obtained through iterative calculation, and the iteration termination condition is that the angle error is less than 0.1 degree or the number of iterations exceeds 10 times.

[0137] 7. Design of wind speed and wind direction error compensator based on feedback control, wind speed compensation coefficient In the range of 0.1-0.5, the wind direction compensation coefficient In the range of 0.2-0.8, when the compensation amount exceeds the preset threshold (wind speed 0.3 m / s, wind direction 3 degrees), the threshold is used for limiting processing.

[0138] After a period of test operation, the wind monitoring system has shown excellent performance in the operating area. Taking the historical data from June 1 to June 30, 2022 as an example, the specific measurement results are shown in the following table: Table 1 Monitoring data of wind monitoring system

[0139] From the data in the table above, it can be seen that the wind monitoring system can accurately record the real-time position, speed, heading of the ship, and key parameters such as the actual wind speed and direction of the environment. By comparing the data of relative wind speed and relative wind direction with the actual wind speed and actual wind direction, it can be found that there is a significant difference between the two, which is mainly due to the influence of the ship's motion state on the wind speed and direction.

[0140] In order to further analyze this influence relationship, the technicians extracted all the measurement data from June 1 to June 30, 2022, and performed detailed analysis and calculation according to steps S20 to S60 of the present invention. First, the ship's speed, heading and relative wind speed data were decomposed into components, and the stable component and the variable component were extracted. Taking the speed as an example, after wavelet analysis, the stable component and variable components , where the threshold of the speed data is 0.5 m / s. Similarly, the stable component of the heading data and variable components and the stable component of the relative wind speed and variable components Also got one after another.

[0141] Then, based on the theory of fluid mechanics, the kinematic correlation function between the ship's speed stability component, heading stability component and relative wind speed variation component was established. Through the least squares fitting method, the coefficients are calculated as , , , the error term of the correlation function exist within the range.

[0142] Next, based on the above motion correlation function, a 3×3 ship motion state matrix is ​​constructed , matrix element , , , , , , , , After performing singular value decomposition on the matrix, the singular value threshold was set to 0.08, successfully eliminating the singularity in the matrix.

[0143] At the same time, based on the wind field analysis theory, a 2×2 environmental wind speed influence matrix was constructed. , where the wind speed influence coefficient is , , wind direction influence coefficient , .

[0144] With the above ship motion state matrix and environmental wind speed influence matrix, the actual wind speed vector can be calculated according to step S60. First, the relative wind speed vector is converted to Then multiply it by two matrices to get the wind speed vector that takes into account the ship motion and environmental influence. Finally, the ship speed vector The wind speed vector is synthesized and passed through Kalman filtering (process noise 0.1, measurement noise 0.05) to obtain the final actual wind speed vector.

[0145] Similarly, according to step S70, the true wind direction angle can be calculated First, extract the x and y components of the actual wind speed vector and use the inverse tangent function to obtain the initial wind direction angle. Then construct a 3×3 optimal path matrix , where the path optimization coefficient , , , , , , , , Based on this matrix, the initial wind direction angle is iteratively optimized. When the angle error is less than 0.08 degrees or after 10 iterations, the corrected true wind direction angle is obtained. .

[0146] Finally, according to step S80, a wind speed and wind direction error compensator based on feedback control is designed. Wind speed compensation coefficient , wind direction compensation coefficient The wind speed error compensation and wind direction error compensation are applied to the actual wind speed vector and true wind direction angle respectively to obtain the corrected wind speed data. and wind direction data When the compensation amount exceeds the preset threshold (wind speed 0.25 m / s, wind direction 2.5 degrees), the threshold is used for limiting processing.

[0147] By performing the above calculations and analysis on all the measurement data from June 1 to June 30, 2022, the technicians obtained the overall performance data of the wind monitoring system, and compared it with the existing traditional wind measurement method based on relative wind speed and heading data. The results are shown in the following table: Table 2 Comparison of performance indicators between traditional wind measurement method and the method of the present invention

[0148] From the comparison in the above table, it can be seen that compared with the traditional wind measurement method based on relative wind speed and heading data, the ship wind measurement method based on single Beidou positioning proposed in the present invention has achieved obvious advantages in measurement cost, measurement accuracy, system complexity and reliability. This is mainly due to the innovation of the present invention in the following aspects: 1. Make full use of the high-precision ship motion status data provided by the Beidou positioning system, avoiding the problem of installing multiple sensors and complex data calibration in traditional methods, thereby greatly reducing system cost and complexity.

[0149] 2. By establishing a coupling relationship model between the ship's motion state and the ambient wind speed and adopting advanced data processing algorithms, the impact of ship motion on wind speed and wind direction measurement is effectively compensated, significantly improving the overall accuracy of the measurement.

[0150] 3. The system structure is simple and compact, no additional sensor equipment needs to be installed, the overall reliability is higher, and it is easy to deploy and maintain on the ship.

[0151] It should be noted that the variables involved in the present invention are explained in detail as shown in Table 3 below.

[0152] Table 3 Variable explanation table

[0153] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A ship wind measurement method based on single Beidou positioning, characterized in that: include: Collect the real-time position data of the ship and the real-time data of the anemometer through the Beidou positioning system; Perform component decomposition calculation on the real-time position data of the ship to obtain the stable speed component and the speed variation component of the ship's speed data, and obtain the stable heading component and the heading variation component of the ship's heading data; perform component decomposition calculation on the real-time data of the anemometer to obtain the stable wind speed component and the wind speed variation component of the relative wind speed data; Establish the motion correlation function of the speed stability component, heading stability component and wind speed variation component, construct the ship motion state matrix; calculate the ship speed vector; construct the environmental wind speed influence matrix; Calculate the actual wind speed vector; Calculate the true wind direction angle; The wind speed error compensation amount and the wind direction error compensation amount are calculated to obtain the corrected wind speed data and the corrected wind direction data.

2. The ship wind measurement method based on single Beidou positioning according to claim 1, characterized in that: The step of collecting the real-time position data of the ship through the Beidou positioning system is specifically to use a Beidou positioning chip to receive Beidou navigation satellite signals, obtain the real-time longitude and latitude data of the ship through differential correction processing, and the sampling frequency of the real-time longitude and latitude data of the ship is 1 Hz; use the Beidou positioning system speed measurement module to calculate the ship speed data; use the Beidou positioning system heading measurement module to calculate the ship heading data; use a dual-axis ultrasonic wind speed and direction sensor to build an anemometer, and calculate the relative wind speed data and relative wind direction data by measuring the ultrasonic propagation time difference between different sensors.

3. The ship wind measurement method based on single Beidou positioning according to claim 2 is characterized in that: The step of performing component decomposition operation on the real-time position data of the ship specifically comprises using a multi-scale wavelet decomposition method to process the ship speed data, selecting a Doppler 4th-order wavelet function as a decomposition basis function, obtaining a low-frequency component of the ship speed data as a speed stability component through a 4-layer wavelet decomposition, and using a high-frequency component of the ship speed data as a speed variation component; and using a Fourier transform method to process the ship heading data; The empirical mode decomposition method is used to process the relative wind speed data.

4. The ship wind measurement method based on single Beidou positioning according to claim 3 is characterized in that: The step of establishing the motion correlation function of the speed stability component, the heading stability component and the wind speed variation component is specifically to establish the motion correlation function of the speed stability component, the heading stability component and the wind speed variation component based on fluid mechanics theory, the motion correlation function includes trigonometric function terms and linear terms, and the coefficients of the trigonometric function terms and the coefficients of the linear terms are calculated by the least squares method; construct a ship motion state matrix according to the motion correlation function, the ship motion state matrix is ​​a 3×3 matrix; and perform singular value decomposition on the ship motion state matrix.

5. The ship wind measurement method based on single Beidou positioning according to claim 4, characterized in that: The step of calculating the ship speed vector specifically comprises decomposing the ship speed data into a longitude speed component and a latitude speed component based on the vector decomposition principle, calculating the longitude speed component and the latitude speed component by trigonometric functions; constructing a rotation matrix considering the influence of the ship heading data, wherein the rotation matrix comprises a heading angle cosine term and a heading angle sine term; The ship velocity vector in the geographic coordinate system is obtained by multiplying the longitude velocity component and the latitude velocity component by the rotation matrix.

6. The ship wind measurement method based on single Beidou positioning according to claim 5, characterized in that: The step of constructing the environmental wind speed influence matrix specifically constructs a 2×2 environmental wind speed influence matrix; The wind speed influence coefficient is calculated. The wind speed influence coefficient is related to the wind speed and the effective area, and is obtained by fitting the wind tunnel test data. The wind direction influence coefficient is calculated. The wind direction influence coefficient is related to the wind direction angle and the shape of the ship, and is obtained by numerical simulation method. The wind speed influence coefficient and the wind direction influence coefficient are combined into an environmental wind speed influence matrix.

7. The ship wind measurement method based on single Beidou positioning according to claim 6, characterized in that: The steps of calculating the actual wind speed vector are specifically to convert the relative wind speed data and the relative wind direction data into a relative wind speed vector; multiply the environmental wind speed influence matrix with the relative wind speed vector to obtain the environmental influence wind speed vector; multiply the ship motion state matrix with the environmental influence wind speed vector to obtain the ship motion influence wind speed vector; synthesize the ship speed vector with the ship motion influence wind speed vector to obtain the actual wind speed vector; and use a Kalman filter to filter the actual wind speed vector.

8. The ship wind measurement method based on single Beidou positioning according to claim 7, characterized in that: The step of calculating the true wind direction angle specifically comprises extracting the longitude component and the latitude component of the actual wind speed vector; calculating the angle between the actual wind speed vector and the true north direction by an inverse tangent function to obtain the initial true wind direction angle; constructing a 3×3 optimal path matrix, and optimizing the optimal path matrix elements by a dynamic programming method; The initial true wind direction angle is iteratively optimized based on the optimal path matrix; the optimized wind direction angle is corrected through statistical analysis of historical data.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program instructions, and when the program instructions are executed in a computer, they are used to execute the ship wind measurement method based on single Beidou positioning according to any one of claims 1 to 8.

10. A ship wind measurement system based on single Beidou positioning, characterized in that: A computer-readable storage medium comprising the computer-readable storage medium of claim 9.

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