Ocean current monitoring method based on submarine mooring subsurface buoy tracking and positioning

Abstract

The invention discloses an ocean current monitoring method based on submarine mooring subsurface buoy tracking and positioning, belongs to the technical field of underwater navigation and positioning, is used for ocean current monitoring, and comprises the following steps: implementing attitude correction of a GNSS (Global Navigation Satellite System) antenna, and obtaining a sound signal emission position of a sea surface transducer; establishing a sea surface-seabed sonar observation equation based on acoustic time measurement data and sound velocity profile data between sea surface and seabed anchor system subsurface buoys, establishing a seabed anchor system subsurface buoy motion constraint equation based on a random walk model, and forming a positioning model considering seabed anchor system subsurface buoy motion characteristics; and carrying out adjustment calculation on the positioning model considering the motion characteristics of the submarine anchor system subsurface buoy to obtain a coordinate sequence of the submarine anchor system subsurface buoy, and carrying out smoothing processing on the coordinate sequence to obtain an ocean current motion trail. According to the invention, the motion sequence of the subsurface buoy is tracked and positioned, so that the motion trail of the ocean current is monitored, and the physical ocean environment of km scale magnitude based on the ocean geodetic survey technology is monitored.

Description

Technical Field

[0001] The present invention discloses a method for monitoring ocean currents based on tracking and positioning of a seabed moored buoy, belonging to the technical field of underwater navigation and positioning. Background Art

[0002] Compared with fixed observation stations, moored observation stations are located at a higher position from the seabed, supporting a wider range of observations and navigation, and having lower economic costs. In addition, underwater moored buoys are very flexible and can be equipped with specific sensors, such as conductivity-temperature-depth (CTD) sensors, acoustic Doppler current profilers (ADCPs), or biological-related sensors, etc., to collect time series data of ocean and meteorological parameters in a specific area. Currently, underwater moored buoys have been widely used in real-time, continuous, and long-term observations and have made important contributions to the research of mesoscale physical ocean environments, such as summer and winter monsoons and tropical cyclones. Based on the advantages of moored beacons in terms of observation range and observation ability, underwater moored buoys equipped with acoustic beacons have potential in remote APN services. Similar to fixed beacons, moored beacons can perform conventional acoustic distance observations through a sea surface platform. However, affected by ocean dynamic factors within the scope of ocean dynamics, real-time motion drive makes it a huge challenge to obtain the accurate position of moored beacons.

[0003] The observation error caused by the spatio-temporal variation of the sound speed structure is one of the key factors affecting the positioning of fixed and moored beacons. The understanding and processing strategies of sound speed information have gone through three stages: single point, vertical profile, and spatio-temporal structure. First, a specific sound speed value (such as weighted average sound speed or harmonic sound speed) is selected, and the time observation is converted into a distance observation through the space intersection method for scenarios with low positioning accuracy requirements in ocean activities. Subsequently, to correct the influence of sound ray bending, a sound speed profile (SSP) is usually adopted, and on the premise of assuming a vertically stratified and equi-gradient SSP, a sound ray tracking method is used. In addition, to meet the requirements of seabed observation network construction and seabed deformation monitoring, a more refined modeling of the sound speed structure is needed. Based on the observation time and the spatial positions of the sea surface platform and the seabed beacon, a sound speed perturbation model in the form of a time-varying linear space function is further proposed. Through this model, the positioning accuracy can be optimized to about 2-3 cm for the horizontal component and about 4-9 cm for the vertical component. It should be noted that the above results are obtained in the scenario of a seabed array composed of fixed beacons. It can be seen that the matching sound speed perturbation model is also crucial for the positioning of the seabed hybrid constellation. The positioning model in the adjustment system is another key point for accurately positioning seabed acoustic beacons. Traditional positioning models have improved the positioning performance to varying degrees. However, all these studies are based on fixed seabed beacons, reasonably ignoring the movement of the beacons, but this is not applicable to moored beacons in the seabed hybrid constellation. Summary of the Invention

[0004] The purpose of the present invention is to provide a sea current monitoring method based on the tracking and positioning of a seabed moored buoy, so as to solve the problem in the prior art that the movement of beacons is often ignored in sea current monitoring, resulting in the inapplicability of moored beacons in the seabed hybrid constellation.

[0005] A sea current monitoring method based on the tracking and positioning of a seabed moored buoy, comprising:

[0006] S1. Obtain the attitude observation data of the position of the GNSS antenna by using an attitude sensor, implement the attitude correction of the GNSS antenna, and obtain the position where the sound signal of the sea surface transducer is emitted;

[0007] S2. Based on the acoustic time measurement data and the sound velocity profile data between the sea surface and the seabed moored buoy, establish a sea surface - seabed sonar observation equation, and establish a motion constraint equation of the seabed moored buoy based on the random walk model, so as to form a positioning model considering the motion characteristics of the seabed moored buoy;

[0008] S3. Conduct adjustment calculation on the positioning model considering the motion characteristics of the seabed moored buoy, obtain the coordinate sequence of the seabed moored buoy, and smooth the coordinate time series to obtain the sea current movement trajectory.

[0009] S1 includes S1.1. Obtain the position of the GNSS receiver on the sea surface carrier , , and are respectively the components of the position of the GNSS receiver on the sea surface carrier in the east direction, north direction, and zenith direction.

[0010] S1 includes S1.2. Obtain the parameters required for GNSS antenna attitude correction through the attitude sensor mounted on the sea surface transducer. The parameters required for GNSS antenna attitude correction include the heading angle , the pitch angle and the roll angle , and establish a coordinate transformation matrix :

[0011] .

[0012] S1 includes S1.3. Utilize the lever arm measurement information between the GNSS receiver and the position where the sound signal of the sea surface transducer is emitted, and calculate the position where the sound signal of the sea surface transducer is emitted :

[0013] ;

[0014] In the formula, , and They are the components of the acoustic signal transmission position of the sea surface transducer in the east, north, and zenith directions, respectively. , and They are the components of the lever arm measurement information of the GNSS receiver and the acoustic signal transmission position of the sea surface transducer in the east, north, and zenith directions, respectively.

[0015] The establishment of the sea surface - seabed sonar observation equation includes:

[0016] ;

[0017] ;

[0018] ;

[0019] ;

[0020] ;

[0021] ;

[0022] In the formula, Observation vector, , are two components of the observation vector, , , are the design matrices, is the diagonal design matrix composed of the fixed beacon model parameter coefficient matrix and the seabed moored buoy model parameter coefficient matrix, is the unknown position parameter related to the static beacon and the seabed moored buoy, is the parameter related to the position of the seabed static station, is the unknown parameter vector related to the position of the seabed moored buoy, is the regularization parameter, is the regularization matrix, is the coefficient matrix of the constraint equation, is the differential operator matrix, is the parameter related to the acoustic velocity structure perturbation, , are two constraint parameters.

[0023] The two constraint parameters satisfy the following:

[0024] ;

[0025] In the formula, represents the calculation of variance, is the standard deviation, is the adjustment factor that controls the relative motion degrees of freedom of the anchor beacon, is the weight matrix of is the weight matrix of the constraint equation.

[0026] Establishing the motion constraint equations of the seabed anchor mooring buoy includes:

[0027] ;

[0028] In the formula, is the position of the seabed anchor mooring buoy at the observation time period , is the serial number index of the seabed anchor mooring buoy, is the random walk error, and the expectation of the random walk error is:

[0029] ;

[0030] The variance of the random walk error is:

[0031] ;

[0032] In the formula, represents the weight matrix of the random walk error.

[0033] The matrix expression of the motion constraint equations of the seabed anchor mooring buoy is:

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] In the formula, is the random walk error matrix.

[0039] The adjustment calculation includes:

[0040] ;

[0041] In the formula, is the -dimensional observation vector for static beacon positioning, is the number of underwater ranging observations, is the Cholesky decomposition matrix, , are random errors;

[0042] Estimate the unknown parameters through the Gauss-Newton iteration formula:

[0043] ;

[0044] wherein, is the estimation of at the iteration, is the estimation of at the iteration. Set the maximum difference between the estimations of the two parameters in two adjacent iterations to be less than the set threshold as the convergence condition.

[0045] The smoothing process includes estimating the Hurst exponent of each component, removing the first components, to obtain the smoothed coordinate sequence :

[0046] ;

[0047] wherein, is the number index of the seabed site, is the total number of seabed sites, represents the coordinate, represents the IMF decomposition of the coordinate, is the time, is the error.

[0048] Compared with the prior art, the present invention has the following beneficial effects: By tracking and positioning the movement time series of the mooring buoy, the monitoring of the sea current movement trajectory is realized, and the monitoring of the physical ocean environment at the km scale is realized based on the marine geodetic technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is the result of the decentralized processing of the movement trajectories of the mooring buoys numbered No. 1 to No. 4;

[0050] Figure 2 is the result of the decentralized processing of the movement trends of the mooring buoys numbered No. 1 to No. 4 in the east-west direction;

[0051] Figure 3 is the result of the decentralized processing of the movement trends of the mooring buoys numbered No. 1 to No. 4 in the north-south direction;

[0052] Figure 4 is the movement trajectory result of the mooring buoy of the position time series of the navigation buoy numbered No. 1;

[0053] Figure 5 It is the movement trajectory result of the mooring buoy for the position time series of the navigation buoy numbered No. 2;

[0054] Figure 6 It is the movement trajectory result of the mooring buoy for the position time series of the navigation buoy numbered No. 3;

[0055] Figure 7 It is the movement trajectory result of the mooring buoy for the position time series of the navigation buoy numbered No. 4. Specific implementation manner

[0056] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] A sea current monitoring method based on seabed mooring buoy tracking and positioning, comprising:

[0058] S1. Obtain the attitude observation data of the position of the GNSS antenna by using an attitude sensor, implement the attitude correction of the GNSS antenna, and obtain the position where the acoustic signal is emitted by the sea surface transducer;

[0059] S2. Based on the acoustic time measurement data and the sound velocity profile data between the sea surface and the seabed mooring buoy, establish a sea surface - seabed sonar observation equation, and establish a movement constraint equation for the seabed mooring buoy based on a random walk model to form a positioning model considering the movement characteristics of the seabed mooring buoy;

[0060] S3. Perform adjustment calculation on the positioning model considering the movement characteristics of the seabed mooring buoy, obtain the coordinate sequence of the seabed mooring buoy, and perform smoothing processing on the coordinate time series to obtain the sea current movement trajectory.

[0061] S1 includes S1.1. Obtain the position of the GNSS receiver on the sea surface carrier , , and are respectively the components of the position of the GNSS receiver on the sea surface carrier in the east direction, north direction and zenith direction.

[0062] S1 includes S1.2. Obtain the parameters required for GNSS antenna attitude correction through the attitude sensor mounted on the sea surface transducer. The parameters required for GNSS antenna attitude correction include the heading angle , pitch angle and roll angle , and establish a coordinate transformation matrix :

[0063] 。

[0064] S1 includes S1.3: measuring the lever arm information of the GNSS receiver and the sound signal transmitting position of the sea surface transducer , and calculating the sound signal transmitting position of the sea surface transducer :

[0065] ;

[0066] In the formula, , and are the components of the sound signal transmitting position of the sea surface transducer in the east, north, and zenith directions respectively, , and are the components of the lever arm measurement information of the GNSS receiver and the sound signal transmitting position of the sea surface transducer in the east, north, and zenith directions respectively.

[0067] Establishing the sea surface - seabed sonar observation equation includes:

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] ;

[0073] ;

[0074] In the formula, observation vector, , are two components of the observation vector, , , are the design matrices, is the diagonal design matrix composed of the fixed beacon model parameter coefficient matrix and the seabed moored buoy model parameter coefficient matrix, is the unknown position parameter related to the static beacon and the seabed moored buoy, is the parameter related to the position of the seabed static station, is the unknown parameter vector related to the position of the seabed moored buoy, is the regularization parameter, is a regularization matrix, is the coefficient matrix of the constraint equation, is the differential operator matrix, is a parameter related to the acoustic velocity structure perturbation, 、 are two constraint parameters.

[0075] The two constraint parameters satisfy the following:

[0076] ;

[0077] In the formula, represents the calculation of variance, is the standard deviation, is an adjustment factor for controlling the relative motion degrees of freedom of the anchor beacon, is the weight matrix of, is the weight matrix of the constraint equation.

[0078] Establishing the motion constraint equation of the seabed moored buoy includes:

[0079] ;

[0080] In the formula, is the position of the seabed moored buoy at the observation time period , is the serial number index of the seabed moored buoy, is the random walk error, and the expectation of the random walk error is:

[0081] ;

[0082] The variance of the random walk error is:

[0083] ;

[0084] In the formula, represents the weight matrix of the random walk error.

[0085] The matrix expression of the motion constraint equation of the seabed moored buoy is:

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] In the formula, is the random walk error matrix.

[0091] The adjustment calculation includes:

[0092] ;

[0093] Wherein, is the -dimensional observation vector for static beacon positioning, is the number of underwater ranging observations, is the Cholesky decomposition matrix, , are random errors;

[0094] Estimate the unknown parameters through the Gauss-Newton iteration formula:

[0095] ;

[0096] Wherein, is the estimation of at the th iteration, is the estimation of at the th iteration. Set the maximum difference between the two parameter estimations in two adjacent iterations to be less than the set threshold as the convergence condition.

[0097] The smoothing process includes estimating the Hurst exponent of each component, removing the first components of to obtain the smoothed coordinate sequence :

[0098] ;

[0099] Wherein, is the index number of the seabed site, is the total number of seabed sites, represents the th coordinate, represents performing IMF decomposition on the th coordinate, is the time, is the error.

[0100] The implementation example of the present invention uses the real observation data during the operation process. In order to evaluate the consistency of the movement between different anchored buoys, the differential processing method is adopted, and the position at the first moment is used as a reference for movement decentralization processing. As Figure 1 shown, the movement amplitude in the west-east direction remains within 4 meters, while the movement amplitude in the north-south direction does not exceed 3 meters, and the trajectory shape is approximately a closed curve. As Figure 2 andFigure 3 As shown, the motion change of the anchored buoy presents a sine wave pattern similar to a cosine wave. Different buoys generally exhibit similar periods, peaks, and valleys. However, some sections of the curve lack the expected smoothness, mainly due to discontinuous observation data. The position of the anchored buoy solved by the ocean current monitoring method, and the motion trajectory is represented by colored dots in Figure 4 , Figure 5 , Figure 6 , Figure 7 . The main motion direction of the anchored buoy is clearly presented, mainly dominated by the east-west motion. Among all the anchored buoys, the initial eastward motion range is 2 meters, and then the westward motion range is 1.5 meters. Figure 5 The arrows in it show this trend. The color bar represents the time series change from the start time to the end time, and the gradually changing orange arrows show the general motion direction of the anchored buoy. Specifically, Navigation Buoys 1 and 3 mainly show an east-west motion trend, while Navigation Buoys 2 and 4 show an approximate northeast-southwest motion trend. However, the current tracking results do not follow any standard or ideal trajectory, which stems from the limitations in the smoothness description of the current motion constraint model in the present invention, and the entire sequence of anchored buoy positions corresponds to three discontinuous time intervals. Using spline basis functions can provide a smoother and more realistic navigation buoy trajectory.

[0101] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features, and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring ocean currents based on the tracking and positioning of a seafloor moored buoy, characterized in that, Including: S1. Obtain the attitude observation data of the GNSS antenna position by using an attitude sensor, implement the attitude correction of the GNSS antenna, and obtain the position where the sound signal of the sea surface transducer is emitted; S2. Based on the acoustic time measurement data and the sound velocity profile data between the sea surface and the seabed moored buoy, establish the sea surface - seabed sonar observation equation, and establish the seabed moored buoy motion constraint equation based on the random walk model to form a positioning model considering the motion characteristics of the seabed moored buoy; S3. Perform adjustment calculation on the positioning model considering the motion characteristics of the seabed moored buoy, obtain the coordinate sequence of the seabed moored buoy, and perform smoothing processing on the coordinate time series to obtain the sea current movement trajectory.

2. The method for monitoring ocean currents based on the tracking and positioning of a seabed moored buoy according to claim 1, characterized in that, S1 includes S1.1, obtaining the position of the GNSS receiver on the sea surface vehicle , , and are the components of the position of the GNSS receiver on the sea surface vehicle in the east, north, and zenith directions, respectively.

3. The method for monitoring ocean currents based on seabed anchor mooring buoy tracking and positioning according to claim 2, characterized in that, S1 includes S1.2, obtaining the parameters required for GNSS antenna attitude correction through the attitude sensor carried on the sea surface transducer. The parameters required for GNSS antenna attitude correction include the heading angle , pitch angle and roll angle , and establishing a coordinate transformation matrix : 。 4. The method for monitoring ocean currents based on tracking and positioning of a seabed moored buoy according to claim 3, wherein, S1 includes S1.3, using the GNSS receiver and the lever arm measurement information of the sea surface transducer acoustic signal transmission position , to calculate the sea surface transducer acoustic signal transmission position : ； In the formula, , and are the components of the sound signal emission position of the sea surface transducer in the east, north, and zenith directions respectively, , and are the components of the lever arm measurement information of the GNSS receiver and the sound signal emission position of the sea surface transducer in the east, north, and zenith directions respectively.

5. The method for monitoring ocean currents based on seabed mooring buoy tracking and positioning according to claim 4, characterized in that, Establishing the sea surface - seabed sonar observation equation includes: ； ； ； ； ； ； In the formula, Observation vector, , are two components of the observation vector, , , are design matrices, is a diagonal design matrix composed of the fixed beacon model parameter coefficient matrix and the seabed moored buoy model parameter coefficient matrix, is the unknown position parameter related to the static beacon and the seabed moored buoy, is the parameter related to the position of the seabed static station, is the unknown parameter vector related to the position of the seabed moored buoy, is the regularization parameter, is the regularization matrix, is the coefficient matrix of the constraint equation, is the differential operator matrix, is the parameter related to the sound speed structure perturbation, , are two constraint parameters.

6. The method for monitoring ocean currents based on subsea mooring buoy tracking and positioning according to claim 5, characterized in that, The two constraint parameters satisfy the following: ； In the formula, represents the calculation of variance, is the standard deviation, is the adjustment factor for controlling the relative motion freedom of the anchor beacon, is the weight matrix of, is the weight matrix of the constraint equation.

7. The method for monitoring ocean currents based on seabed mooring buoy tracking and positioning according to claim 6, wherein, Establishing the seabed moored buoy motion constraint equation includes: ； In the formula, is the position of the seabed moored subsurface buoy at the observation time , is the serial number index of the seabed moored subsurface buoy, is the random walk error, and the expectation of the random walk error is: ； Variance of the random walk error is as follows: ； In the formula, represents the weight matrix of the random walk error.

8. The method for monitoring ocean currents based on subsea mooring buoy tracking and positioning according to claim 7, wherein The matrix expression of the seabed moored buoy motion constraint equation is: ； ； ； ； In the formula, is the random walk error matrix.

9. The method for monitoring ocean currents based on subsea mooring buoy tracking and positioning according to claim 8, wherein, The adjustment calculation includes: ； wherein, is the -dimensional observation vector for static beacon positioning, is the number of underwater ranging observations, is the Cholesky decomposition matrix, , are random errors; Estimate the unknown parameters through the Gauss - Newton iteration formula: ； wherein, is the -th iteration of the estimate, is the -th iteration of the estimate, and the maximum difference between the two parameter estimates in two adjacent iterations is set to be less than a set threshold as the convergence condition.

10. A method for monitoring ocean currents based on tracking and positioning of a seafloor moored buoy according to claim 9, characterized in that, The smoothing process includes estimating the Hurst exponent of each component and removing the first components to obtain the smoothed coordinate sequence : ； In the formula, is the serial number index of the seabed site, is the total number of seabed sites, represents the th coordinate, represents performing IMF decomposition on the th coordinate, is the time, is the error.

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