Submarine node positioning method and device based on ultra-short base line

Abstract

The invention discloses a seabed node positioning method and device based on an ultra-short baseline. The method comprises the steps that an observation vector correction matrix of first positioning time is generated according to a probe coordinate observation value and a relative coordinate observation value of the first positioning time and a node coordinate correction number of second positioning time, the first positioning time is current time, and the second positioning time is previous positioning time of the first positioning time; generating a gain matrix of the first positioning time according to the variance and covariance matrix of the second positioning time; calculating a node coordinate correction number of the first positioning time according to the gain matrix and the observation vector correction matrix of the first positioning time and the node coordinate correction number of the second positioning time; and generating a node coordinate of the first positioning time according to the node coordinate of the second positioning time and the node coordinate correction number of the first positioning time. By adopting the scheme, real-time positioning of the seabed node can be realized, and the positioning efficiency of the seabed node is improved.

Description

Technical Field

[0001] The present application relates to the field of exploration technology, and in particular to a method, device, computing equipment, computer storage medium and computer program product for positioning a seabed node based on an ultra-short baseline. Background Art

[0002] Ultra-short baseline (USBL) is an underwater positioning technology that installs a transponder on the target to be located underwater and an ultra-short baseline array on the hull above water. The transponder sends out an acoustic signal, and the ultra-short baseline system calculates the direction and distance of the target after receiving the signal.

[0003] Ultra-short baselines are widely used in seabed node positioning in marine exploration due to their simple structure. However, the existing technology has low positioning efficiency when using ultra-short baselines to locate seabed nodes, and cannot determine the position of seabed nodes in real time. Summary of the invention

[0004] In view of the above problems, the present application is proposed to provide a method, apparatus, computing device, computer storage medium and computer program product for seabed node positioning based on ultra-short baseline that overcome the above problems or at least partially solve the above problems.

[0005] According to a first aspect of the present application, a method for positioning a seafloor node based on an ultra-short baseline is provided, comprising:

[0006] Obtaining the probe coordinate observation value and relative coordinate observation value of the first positioning time; wherein the first positioning time is the current time;

[0007] Obtaining node coordinates, node coordinate corrections, and variance-covariance matrices of a second positioning time obtained in advance based on sequential adjustment; wherein the second positioning time is a previous positioning time of the first positioning time;

[0008] Generate an observation vector correction matrix at the first positioning time according to the probe coordinate observation value and the relative coordinate observation value at the first positioning time and the node coordinate correction number at the second positioning time;

[0009] Generate a gain matrix at the first positioning time according to the variance-covariance matrix at the second positioning time;

[0010] Calculate the node coordinate correction number of the first positioning time according to the gain matrix and the observation vector correction matrix of the first positioning time and the node coordinate correction number of the second positioning time;

[0011] The node coordinates at the first positioning time are generated according to the node coordinates at the second positioning time and the node coordinate correction number at the first positioning time.

[0012] In an optional implementation, generating an observation vector correction matrix at the first positioning time according to the probe coordinate observation value and the relative coordinate observation value at the first positioning time and the node coordinate correction number at the second positioning time includes:

[0013] Obtain the coefficient matrix and closure error of the first positioning time;

[0014] Calculate the product of the coefficient matrix of the first positioning time and the node coordinate correction number of the second positioning time;

[0015] The observation vector correction matrix of the first positioning time is obtained according to the difference between the closure error and the product.

[0016] In an optional implementation, generating a gain matrix of the first positioning time according to the variance-covariance matrix of the second positioning time includes:

[0017] A gain matrix at the first positioning time is generated according to the variance-covariance matrix at the second positioning time and the coefficient matrix at the first positioning time.

[0018] In an optional implementation, the calculating the node coordinate correction number of the first positioning time according to the gain matrix and the observation vector correction matrix of the first positioning time and the node coordinate correction number of the second positioning time includes:

[0019] Calculate the product of the gain matrix of the first positioning time and the observation vector correction matrix;

[0020] The node coordinate correction number at the first positioning time is generated according to the sum of the node coordinate correction number at the second positioning time and the product.

[0021] In an optional implementation, obtaining the probe coordinate observation value at the first positioning time includes:

[0022] Obtaining the DGPS observation value associated with the first positioning time;

[0023] Preprocessing the DGPS observation value to obtain the probe coordinate observation value of the first positioning time;

[0024] The preprocessing includes one or more of the following processing methods: epoch synchronization processing, threshold gross error filtering processing, bidirectional gross error filtering processing, and coordinate conversion processing.

[0025] In an optional implementation, the bidirectional gross error filtering process includes:

[0026] For any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the next DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the next DGPS observation value to the forward verification set;

[0027] For any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the previous DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the previous DGPS observation value to the negative verification set;

[0028] Overlapping data in the positive validation set and the negative validation set are identified as gross errors.

[0029] According to a second aspect of the present application, a submarine node positioning device based on an ultra-short baseline is provided, comprising:

[0030] An observation value acquisition module is used to acquire the probe coordinate observation value and the relative coordinate observation value of the first positioning time; wherein the first positioning time is the current time;

[0031] A solution result acquisition module is used to obtain the node coordinates, node coordinate correction numbers, and variance-covariance matrix of the second positioning time obtained in advance based on the sequential adjustment solution; wherein the second positioning time is the previous positioning time of the first positioning time;

[0032] The solution module is used to generate an observation vector correction matrix at the first positioning time according to the probe coordinate observation value and the relative coordinate observation value at the first positioning time, and the node coordinate correction number at the second positioning time; generate a gain matrix at the first positioning time according to the variance covariance matrix at the second positioning time; calculate the node coordinate correction number at the first positioning time according to the gain matrix and the observation vector correction matrix at the first positioning time, and the node coordinate correction number at the second positioning time; generate the node coordinates at the first positioning time according to the node coordinates at the second positioning time and the node coordinate correction number at the first positioning time.

[0033] In an optional embodiment, the solution module is used to: obtain the coefficient matrix and closure error of the first positioning time; calculate the product of the coefficient matrix of the first positioning time and the node coordinate correction number of the second positioning time; and obtain the observation vector correction matrix of the first positioning time based on the difference between the closure error and the product.

[0034] In an optional implementation, the solving module is used to generate a gain matrix of the first positioning time according to the variance-covariance matrix of the second positioning time and the coefficient matrix of the first positioning time.

[0035] In an optional implementation, the solution module is used to: calculate the product of the gain matrix of the first positioning time and the observation vector correction matrix;

[0036] The node coordinate correction number at the first positioning time is generated according to the sum of the node coordinate correction number at the second positioning time and the product.

[0037] In an optional implementation, the solution module is used to: obtain a DGPS observation value associated with the first positioning time;

[0038] Preprocessing the DGPS observation value to obtain the probe coordinate observation value of the first positioning time;

[0039] The preprocessing includes one or more of the following processing methods: epoch synchronization processing, threshold gross error filtering processing, bidirectional gross error filtering processing, and coordinate conversion processing.

[0040] In an optional implementation, the solution module is used to: for any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the next DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds a preset threshold, add the next DGPS observation value to the forward verification set;

[0041] For any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the previous DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the previous DGPS observation value to the negative verification set;

[0042] Overlapping data in the positive validation set and the negative validation set are identified as gross errors.

[0043] According to a third aspect of the present application, there is provided a computing device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0044] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned seabed node positioning method based on ultra-short baseline.

[0045] According to a fourth aspect of the present application, a computer storage medium is provided, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables a processor to perform operations corresponding to the above-mentioned seabed node positioning method based on ultra-short baseline.

[0046] According to a fifth aspect of the present application, a computer program product is provided, comprising at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the above-mentioned method for positioning a seabed node based on an ultra-short baseline.

[0047] In the method, device, computing equipment, computer storage medium and computer program product for positioning seabed nodes based on ultra-short baseline provided by the present application, the observation vector correction matrix of the first positioning time is generated according to the probe coordinate observation value and relative coordinate observation value of the first positioning time, and the node coordinate correction number of the second positioning time, the first positioning time is the current time, and the second positioning time is the previous positioning time of the first positioning time; the gain matrix of the first positioning time is generated according to the variance covariance matrix of the second positioning time; the node coordinate correction number of the first positioning time is calculated according to the gain matrix and observation vector correction matrix of the first positioning time, and the node coordinate correction number of the second positioning time; the node coordinate of the first positioning time is generated according to the node coordinate of the second positioning time and the node coordinate correction number of the first positioning time. The adoption of this scheme can realize the real-time positioning of seabed nodes and improve the positioning efficiency of seabed nodes.

[0048] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0050] Figure 1 A flow chart of a method for positioning a seabed node based on an ultra-short baseline provided in Embodiment 1 of the present application is shown;

[0051] Figure 2 A flow chart of a method for positioning a seabed node based on an ultra-short baseline provided in Embodiment 2 of the present application is shown;

[0052] Figure 3 A flow chart of a forward verification method provided in Embodiment 2 of the present application is shown;

[0053] Figure 4 A structural diagram of a seabed node positioning device based on an ultra-short baseline provided in Embodiment 3 of the present application is shown;

[0054] Figure 5A structural diagram of a computing device provided in Embodiment 4 of the present application is shown. DETAILED DESCRIPTION

[0055] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0056] Embodiment 1

[0057] Figure 1 FIG. 1 is a flow chart of a method for positioning a submarine node based on an ultra-short baseline provided in the first embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0058] Step S101, obtaining the probe coordinate observation value and the relative coordinate observation value of the first positioning time; wherein the first positioning time is the current time.

[0059] The present application uses a USBL positioning system to locate the seabed node to be located. The USBL positioning system includes an acoustic probe, an acoustic array, and an underwater transponder. Among them, the acoustic array is composed of at least three hydrophones arranged according to corresponding rules, and the distance between the hydrophones is usually only a few centimeters. The USBL positioning system measures the distance and direction from the probe to the seabed node by sending and receiving acoustic signals, thereby obtaining the relative coordinates between the USBL acoustic probe and the seabed node. The present application refers to the relative coordinates between the USBL acoustic probe and the seabed node obtained by the USBL positioning system as relative coordinate observation values.

[0060] In addition, the USBL acoustic probe is usually installed on an exploration ship, so that the absolute position of the shipborne USBL probe can be obtained through the global differential positioning system (DGNSS), shipborne attitude sensor, and / or gyrocompass and other equipment installed on the exploration ship. In this application, the measured absolute position of the USBL probe is referred to as the probe coordinate observation value.

[0061] When the position of the seabed node needs to be determined, the current time is used as the first positioning time, and the probe coordinate observation value and the relative coordinate observation value of the first positioning time are obtained. In the embodiment of the present application, in order to improve the positioning accuracy of the seabed node, the probe coordinate observation value and the relative coordinate observation value of each positioning time can be multiple groups, so that the first positioning time can include multiple groups of observation values, each group of observation values ​​includes the probe coordinate observation value and the relative coordinate observation value.

[0062] In the following, this application is based on the sequential adjustment algorithm, combining multiple sets of measurement values ​​at the current time and the sequential adjustment results of the historical time to calculate the seabed node coordinates at the current time in real time. The specific derivation process is as follows:

[0063]

[0064] Among them, V k-1 represents the error variance of the k-1th period, V k represents the error variance of the kth period, B k-1 represents the coefficient matrix of the k-1th period, B k represents the coefficient matrix of the kth period, represents the node coordinate correction number of the k-1th period, represents the node coordinate correction number of the kth period, l k-1 represents the closure error of the k-1th period, l k represents the closure error of the kth period.

[0065] The following formulas 3 and 4 can be obtained by adjusting the k-th period observations separately:

[0066]

[0067] in, represents the variance-covariance matrix of the k-1th period, B k-1 represents the coefficient matrix of the k-1th period, P k-1 represents the identity matrix of the k-1th period, l k-1 represents the closure error of the k-1th period.

[0068] Combining formulas 1-4, we can get the observation equation for the kth period, as shown in formula 5:

[0069]

[0070] in, Indicates the node coordinate correction number of the kth period; represents the node coordinate correction number of the k-1th period; J k represents the gain matrix of the kth period, which can be shown as formula 6; represents the observation vector correction matrix of the kth period, which can be shown as formula 7.

[0071]

[0072] Among them, the variance-covariance matrix relationship between the kth period and the k-1th period can be shown as formula 8:

[0073]

[0074] Step S102, obtaining the node coordinates, node coordinate corrections, and variance-covariance matrix of the second positioning time pre-calculated based on the sequential adjustment algorithm; wherein the second positioning time is the previous positioning time of the first positioning time.

[0075] The embodiment of the present application is based on the sequential adjustment algorithm to solve the node coordinates of different positioning times in real time. The sequential adjustment algorithm is also called the successive correlation indirect adjustment, which divides the observation values ​​into two groups and performs the related indirect adjustment in the order of the groups. In the present application, the current time is divided into one group, and the historical time is divided into another group for sequential adjustment, so that the node coordinates of the seabed node at the current time can be solved in real time.

[0076] In this application, the second positioning time is the previous positioning time of the current time, and the second positioning time can be called the most recent historical positioning time of the current time. Since the second positioning time is a historical time, the node coordinates of the second positioning time at the current time are known, and the node coordinates of the second positioning time refer to the coordinates of the seabed node at the second timing time calculated by the method of this application. When calculating the node coordinates of the first positioning time, the node coordinates of the second positioning time are obtained.

[0077] In addition, the present application also obtains the node coordinate correction number and the variance covariance matrix of the second positioning time, wherein the node coordinate correction number of the second positioning time is the correction amount to the node approximate coordinates of the second positioning time, and the variance covariance matrix of the second positioning time is related to the coefficient matrix of the second positioning time, and the node coordinate correction number and the variance covariance matrix are obtained during the node coordinate solution process of the second positioning time, so this step can directly obtain the node coordinates, node coordinate correction number and variance covariance matrix of the second positioning time.

[0078] Step S103, generating an observation vector correction matrix of the first positioning time according to the probe coordinate observation value and the relative coordinate observation value of the first positioning time and the node coordinate correction number of the second positioning time.

[0079] The observation values ​​of the first positioning time (including the probe coordinate observation values ​​and the relative coordinate observation values) and the node coordinate correction numbers of the second positioning time are combined to generate the observation vector correction matrix of the first positioning time.

[0080] In an optional implementation manner, the observation vector correction matrix of the first positioning time is generated specifically by the following steps:

[0081] (1) Obtain the coefficient matrix of the first positioning time.

[0082] The coefficient matrix in this application is shown in Formula 9:

[0083]

[0084] Among them, B k is the coefficient matrix of the first positioning time, which is a 3*n matrix, where n represents the number of observation value groups corresponding to the first positioning time, and each element in the matrix is ​​1.

[0085] (2) Obtain the closing error of the first positioning time.

[0086] The closure error in this application is shown in formula 10:

[0087]

[0088] Among them, l k Indicates the closing error of the first positioning time, (X k-1 , Y k-1 , Z k-1 ) represents the node coordinates at the second positioning time, (Δx1, Δy1, Δz1) represents the first set of relative coordinate observations at the first positioning time, (Δx n , Δy n , Δz n ) represents the nth group of relative coordinate observations at the first positioning time, (X1, Y1, Z1) represents the first group of probe coordinate observations at the first positioning time, (X n , Y n , Z n ) represents the nth group of probe coordinate observation values ​​at the first positioning time.

[0089] (3) Calculate the product of the coefficient matrix of the first positioning time and the node coordinate correction number of the second positioning time, and obtain the observation vector correction matrix of the first positioning time according to the difference between the closure error and the product.

[0090] That is, the observation vector correction matrix can be shown as formula 7, that is, the coefficient matrix B for calculating the first positioning time k Node coordinate correction number with the second positioning time The product of The difference between the misclosure and the product As the observation vector correction matrix of the first positioning time

[0091] Step S104: Generate a gain matrix for the first positioning time according to the variance-covariance matrix for the second positioning time.

[0092] Specifically, the gain matrix of the first positioning time is generated according to the variance covariance matrix of the second positioning time and the coefficient matrix of the first positioning time. Referring to Formula 6, according to the variance covariance matrix of the second positioning time The coefficient matrix B of the first positioning time k , the unit matrix P of the first positioning timek Generate the gain matrix J for the first positioning time k .

[0093] In addition, further optionally, referring to Formula 8, when obtaining the gain matrix J at the first positioning time k Then, according to the variance covariance matrix of the second positioning time The gain matrix J of the first positioning time k , and the coefficient matrix B of the first positioning time k Generate the variance-covariance matrix of the first positioning time For subsequent use based on the variance covariance matrix of the first positioning time Carry out the seabed node positioning for the next positioning time. Correspondingly, the variance covariance matrix of the current second positioning time is in, represents the variance-covariance matrix of the third positioning time, J k-1 represents the gain matrix of the second positioning time, B k-1 A coefficient matrix representing the second positioning time.

[0094] Step S105 , calculating the node coordinate correction number of the first positioning time according to the gain matrix and the observation vector correction matrix of the first positioning time and the node coordinate correction number of the second positioning time.

[0095] Specifically, referring to Formula 5, the gain matrix J of the first positioning time is calculated as k and the observation vector correction matrix The product of Node coordinate correction number based on the second positioning time and the product The sum of the node coordinate corrections for the first positioning time is generated

[0096] Step S106: Generate the node coordinates at the first positioning time according to the node coordinates at the second positioning time and the correction number of the node coordinates at the first positioning time.

[0097] Specifically, the sum of the node coordinates of the second positioning time and the node coordinate correction number of the first positioning time is used as the node coordinates of the first positioning time. That is, the node coordinates of the second positioning time are used as the approximate value of the first positioning time, and the node coordinate correction number of the first positioning time is used to correct the approximate value to obtain the final node coordinates of the first positioning time.

[0098] For details, please refer to the following formula 11:

[0099]

[0100] in, represents the node coordinates at the first positioning time, represents the node coordinates at the second positioning time, Indicates the node coordinate correction number at the first positioning time.

[0101] It can be seen that the solution process of each step of the present application is simple, the solution workload is low, and the solution efficiency is high.

[0102] It can be seen that the seabed node positioning method based on the ultra-short baseline provided in the embodiment of the present application can quickly and accurately determine the node coordinates at the current time according to the solution results of the historical time and the observation values ​​of the current time, realize the real-time positioning of the seabed node, and improve the positioning accuracy of the seabed node.

[0103] Embodiment 2

[0104] Figure 2 The flowchart of a method for positioning a seafloor node based on an ultra-short baseline provided in the second embodiment of the present application is shown. The embodiment of the present application mainly improves the processing process of the observation value.

[0105] Specifically, Figure 2 As shown, the method comprises the following steps:

[0106] Step S201, collecting navigation data.

[0107] The navigation data in the embodiment of the present application may include DGPS observation values, and may also include depth sounder observation values ​​and gyro compass observation values, etc.

[0108] Step S202, pre-processing the navigation data to obtain probe coordinate observation values.

[0109] Specifically, a DGPS observation value associated with the first positioning time is obtained. The DGPS observation value associated with the first positioning time is a DGPS observation value that can be used to determine the first positioning time, for example, it can be a DGPS observation value after the second positioning time.

[0110] The DGPS observation values ​​are further preprocessed to obtain the probe coordinate observation values ​​of the first positioning time; wherein the preprocessing includes one or more of the following processing methods: epoch synchronization processing, threshold gross error filtering processing, bidirectional gross error filtering processing, and coordinate conversion processing.

[0111] Epoch synchronization processing refers to unifying the DGPS observation values ​​at different observation times to the first positioning time. Specifically, due to the different sampling rates and observation epochs of each positioning device, in order to return its observation values ​​to the calculation time t c(i.e., the first positioning time), it is necessary to synchronize the epoch. For example, the cached historical data (using the historical observations of each observation value stored in a fixed-length sliding window) can be fitted using a polynomial fitting method, such as using formula 12 for data fitting:

[0112] x(t)=a0+a1t+a2t 2 +…+a n t n (Formula 12)

[0113] Among them, a0…a n are the polynomial coefficients, and n is the polynomial order. After determining the polynomial coefficients using the least squares estimate, t = t c Substituting into the above formula, we can obtain t c The observed value corresponding to the time.

[0114] Threshold gross error filtering is to set a change rate gross error threshold, and filter the observations whose change rate exceeds the set change rate gross error threshold. The change rate can be calculated by the following formula:

[0115] Formula 13 is used to calculate:

[0116]

[0117] Among them, r i,j is the observed value t i Time to t j The average rate of change at time, x i is the historical data, x j is the new data. If the observed value change rate r i,j If the observed value x exceeds the set threshold, j If there is a gross error in the observation, the observation can be filtered out. This filtering method is usually used to filter out large gross errors.

[0118] Bidirectional gross error filtering is used to filter small gross errors. Different from the traditional gross error filtering method, in order to improve the filtering accuracy of small gross errors and reduce the misjudgment rate, the specific implementation method of the bidirectional gross error filtering is as follows:

[0119] For any observation value in the observation value sequence composed of observation values, the median corresponding to the observation value is calculated, so that a median sequence composed of various medians can be obtained. For example, the median sequence can be calculated by the following formula 14:

[0120]

[0121] in, For x i The observation sequence, y i For xi The median of the observed sequence is also x i The corresponding median, m is the observation sequence window length, which is generally an odd number. The number of medians is consistent with the number of observations. The window size m can be set according to the observation type and is generally an odd number.

[0122] For any observation x i , for the observed value x i Perform positive verification. For the verification process, see Figure 3 For any DGPS observation, calculate the observation change rate and median change rate of the DGPS observation and the next DGPS observation, calculate the absolute value of the difference between the observation change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the next DGPS observation to the forward verification set.

[0123] The change rate of the observed values ​​between data i and data j can refer to formula 15:

[0124]

[0125] Among them, dx i,j represents the rate of change of observations between data i and data j, x i Represents data i, x j Represents data j, t j -t i Represents the serial interval or sampling time interval between data i and data j.

[0126] The median change rate corresponding to data i and data j can refer to formula 16:

[0127]

[0128] Among them, dy i,j Indicates the median change rate between data i and data j, y i Indicates the median corresponding to data i, y j Represents the median corresponding to data j.

[0129] If |dy i,j -dx i,j | exceeds the preset threshold, then the data j(x j ) may contain gross errors, and the data with gross errors are added to the forward validation set.

[0130] Correspondingly, when performing reverse verification, for any DGPS observation value, the observation value change rate and median change rate of the DGPS observation value and the previous DGPS observation value are calculated, and the absolute value of the difference between the observation value change rate and the median change rate is calculated. If the absolute value of the difference exceeds the preset threshold, the previous DGPS observation value is added to the negative verification set. For example, Figure 3 After the change to start, i = n, j = n-1, if |dy i,j -dx i,j | does not exceed the predetermined threshold, then i = j, j = j-1, and make subsequent judgments; if |dy ii,j -dx i,j | exceeds a predetermined threshold, then the data j(x j ) may contain gross errors, and the data with gross errors are added to the negative validation set.

[0131] Finally, the overlapping data in the positive validation set and the negative validation set are determined as gross errors and eliminated.

[0132] The coordinate conversion is specifically: converting the original geodetic coordinates into plane projection coordinates. For example, the following UTM projection forward calculation formula (such as formula 16) can be used for conversion:

[0133]

[0134] Among them, (X, Y) are the plane projection coordinates of the point; (B, L) are the geodetic coordinates of the point; l(B) is the meridian arc length from the equator to the projection point; N is the radius of the meridian circle; t=tan(B); η=e′cos(B), e′ is the second eccentricity of the reference ellipsoid; l=L-L0 is the longitude difference, and L0 is the longitude of the central meridian of the projection zone.

[0135] After obtaining the plane coordinates of the DGPS points of the survey ship, the coordinates of the USBL probe on the survey ship can be calculated using the design offset of each node in the ship coordinate system, as shown in Formula 17:

[0136]

[0137] Among them, (X p ,Y p ) is the USBL probe coordinate; α v dx is the azimuth of the bow, obtained by Gyro (electric compass); offset ,dy offset is the design offset of the USBL probe relative to the DGPS node in the ship coordinates, given by the configuration; (X DGPS ,Y DGPS ) are the DGPS node coordinates.

[0138] The probe coordinate measurement value can be obtained through the above operation.

[0139] Step S203, obtaining the relative coordinate observation value of the first positioning time.

[0140] The USBL positioning system measures the distance and direction from the probe to the seabed node by sending and receiving acoustic signals, thereby obtaining the relative coordinates between the USBL acoustic probe and the seabed node. The positioning principle is as follows:

[0141] The angle θ between the center of the acoustic array and the underwater transponder in three directions x ,θ y ,θ z The cosine value is:

[0142]

[0143] Where λ is the wavelength of the sound wave; b is the distance between array units; are the phase differences received between two array units.

[0144] The relative coordinates (Δx, Δy, Δz) between the USBL probe and the seafloor node are:

[0145]

[0146] Where R is the distance from the center of the acoustic array to the underwater transponder.

[0147] Step S204, calculating the node coordinates at the first positioning time based on the probe coordinate observation value and the relative coordinate observation value at the first positioning time and the node coordinates, node coordinate correction number, and variance-covariance matrix at the second positioning time.

[0148] The specific calculation process refers to the description in other embodiments and will not be repeated here.

[0149] It can be seen that the seabed node positioning method based on the ultra-short baseline provided in the embodiment of the present application can accurately filter out small gross errors and improve the seabed node positioning accuracy through forward and reverse verification methods.

[0150] Embodiment 3

[0151] Figure 4 FIG. 1 shows a structural diagram of a submarine node positioning device based on an ultra-short baseline provided in Embodiment 3 of the present application. Figure 4 As shown, the device 400 includes: an observation value acquisition module 410, a solution result acquisition module 420, and a solution module 430.

[0152] The observation value acquisition module 410 is used to acquire the probe coordinate observation value and the relative coordinate observation value of the first positioning time; wherein the first positioning time is the current time;

[0153] The solution result acquisition module 420 is used to obtain the node coordinates, node coordinate corrections, and variance-covariance matrix of the second positioning time obtained in advance based on the sequential adjustment solution; wherein the second positioning time is the previous positioning time of the first positioning time;

[0154] The solution module 430 is used to generate an observation vector correction matrix at the first positioning time based on the probe coordinate observation value and the relative coordinate observation value at the first positioning time, and the node coordinate correction number at the second positioning time; generate a gain matrix at the first positioning time based on the variance covariance matrix at the second positioning time; calculate the node coordinate correction number at the first positioning time based on the gain matrix and the observation vector correction matrix at the first positioning time, and the node coordinate correction number at the second positioning time; generate the node coordinates at the first positioning time based on the node coordinates at the second positioning time and the node coordinate correction number at the first positioning time.

[0155] In an optional embodiment, the solution module 430 is used to: obtain the coefficient matrix and closure error of the first positioning time; calculate the product of the coefficient matrix of the first positioning time and the node coordinate correction number of the second positioning time; and obtain the observation vector correction matrix of the first positioning time based on the difference between the closure error and the product.

[0156] In an optional implementation, the solving module 430 is used to generate a gain matrix of the first positioning time according to the variance-covariance matrix of the second positioning time and the coefficient matrix of the first positioning time.

[0157] In an optional implementation, the solution module 430 is used to: calculate the product of the gain matrix of the first positioning time and the observation vector correction matrix;

[0158] The node coordinate correction number at the first positioning time is generated according to the sum of the node coordinate correction number at the second positioning time and the product.

[0159] In an optional implementation, the solution module 430 is used to: obtain a DGPS observation value associated with the first positioning time;

[0160] Preprocessing the DGPS observation value to obtain the probe coordinate observation value of the first positioning time;

[0161] The preprocessing includes one or more of the following processing methods: epoch synchronization processing, threshold gross error filtering processing, bidirectional gross error filtering processing, and coordinate conversion processing.

[0162] In an optional implementation, the solution module 430 is used to: for any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the next DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds a preset threshold, add the next DGPS observation value to the forward verification set;

[0163] For any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the previous DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the previous DGPS observation value to the negative verification set;

[0164] Overlapping data in the positive validation set and the negative validation set are identified as gross errors.

[0165] It can be seen that the seabed node positioning method based on the ultra-short baseline provided in the embodiment of the present application can quickly and accurately determine the node coordinates at the current time according to the solution results of the historical time and the observation values ​​of the current time, realize the real-time positioning of the seabed node, and improve the positioning accuracy of the seabed node.

[0166] Embodiment 4

[0167] Figure 5 The structure diagram of a computing device provided in the fourth embodiment of the present application is shown. The specific embodiments of the present application do not limit the specific implementation of the computing device.

[0168] like Figure 5 As shown, the computing device may include: a processor (processor) 502 , a communications interface (Communications Interface) 504 , a memory (memory) 506 , and a communication bus 508 .

[0169] The processor 502, the communication interface 504, and the memory 506 communicate with each other via a communication bus 508. The communication interface 504 is used to communicate with other devices such as a client or other server network elements. The processor 502 is used to execute a program 510, which can specifically execute the relevant steps in the above-mentioned embodiment of the method for positioning a submarine node based on an ultra-short baseline for a computing device.

[0170] Specifically, the program 510 may include program codes, which include computer operation instructions.

[0171] The processor 502 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0172] The memory 506 is used to store the program 510. The memory 506 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory. The program 510 may be specifically used to enable the processor 502 to perform the operations in the above method embodiment.

[0173] Embodiment 5

[0174] Embodiment 5 of the present application provides a non-volatile computer storage medium, which stores at least one executable instruction or computer program, and the executable instruction or computer program enables the processor to perform operations corresponding to the seabed node positioning method based on ultra-short baseline in any of the above method embodiments.

[0175] Embodiment 6

[0176] Embodiment 6 of the present application provides a computer program product, which includes at least one executable instruction or computer program, which enables a processor to perform operations corresponding to the ultra-short baseline-based seabed node positioning method in any of the above-mentioned method embodiments.

[0177] In summary, according to the computing device, computer storage medium and computer program product provided by this embodiment, the node coordinates at the current time can be quickly and accurately determined based on the solution results of the historical time and the observation values ​​at the current time, so as to realize the real-time positioning of the seabed node and improve the positioning accuracy of the seabed node.

[0178] The algorithm or display provided here are not inherently related to any specific computer, virtual system or other equipment. Various general systems can also be used together with the teaching based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described here, and the above description of specific languages ​​is to disclose the best mode of implementation of the present application.

[0179] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0180] Similarly, it should be understood that in order to streamline the present application and help understand one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the embodiments of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be interpreted as reflecting the following intention: the claimed application requires more features than the features clearly stated in each claim. More specifically, as reflected in the claims below, the inventive aspects are less than all the features of the single embodiment disclosed above. Therefore, the claims following the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself serves as a separate embodiment of the present application.

[0181] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0182] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0183] The various component embodiments of the present application can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some or all components according to the embodiments of the present application. The application can also be implemented as a device or apparatus program (e.g., computer program and computer program product) for executing a part or all of the methods described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0184] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be constructed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A method for positioning seabed nodes based on ultra-short baselines, characterized in that: include: Obtaining the probe coordinate observation value and relative coordinate observation value of the first positioning time; wherein the first positioning time is the current time; Obtaining node coordinates, node coordinate corrections, and variance-covariance matrices of a second positioning time obtained in advance based on sequential adjustment; wherein the second positioning time is a previous positioning time of the first positioning time; Generate an observation vector correction matrix at the first positioning time according to the probe coordinate observation value and the relative coordinate observation value at the first positioning time and the node coordinate correction number at the second positioning time; Generate a gain matrix at the first positioning time according to the variance-covariance matrix at the second positioning time; Calculate the node coordinate correction number of the first positioning time according to the gain matrix and the observation vector correction matrix of the first positioning time and the node coordinate correction number of the second positioning time; The node coordinates at the first positioning time are generated according to the node coordinates at the second positioning time and the node coordinate correction number at the first positioning time.

2. The method according to claim 1, characterized in that The step of generating an observation vector correction matrix at the first positioning time according to the probe coordinate observation value and the relative coordinate observation value at the first positioning time and the node coordinate correction number at the second positioning time comprises: Obtain the coefficient matrix and closure error of the first positioning time; Calculate the product of the coefficient matrix of the first positioning time and the node coordinate correction number of the second positioning time; The observation vector correction matrix of the first positioning time is obtained according to the difference between the closure error and the product.

3. The method according to claim 1, characterized in that The step of generating a gain matrix for the first positioning time according to the variance-covariance matrix for the second positioning time comprises: A gain matrix at the first positioning time is generated according to the variance-covariance matrix at the second positioning time and the coefficient matrix at the first positioning time.

4. The method according to any one of claims 1 to 3, characterized in that The calculating of the node coordinate correction number of the first positioning time according to the gain matrix and the observation vector correction matrix of the first positioning time and the node coordinate correction number of the second positioning time comprises: Calculate the product of the gain matrix of the first positioning time and the observation vector correction matrix; The node coordinate correction number at the first positioning time is generated according to the sum of the node coordinate correction number at the second positioning time and the product.

5. The method according to any one of claims 1 to 3, characterized in that: The acquisition of the probe coordinate observation value at the first positioning time includes: Obtaining the DGPS observation value associated with the first positioning time; Preprocessing the DGPS observation value to obtain the probe coordinate observation value of the first positioning time; The preprocessing includes one or more of the following processing methods: epoch synchronization processing, threshold gross error filtering processing, bidirectional gross error filtering processing, and coordinate conversion processing.

6. The method according to claim 5, characterized in that The bidirectional gross error filtering process includes: For any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the next DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the next DGPS observation value to the forward verification set; For any DGPS observation value, calculate the observation value change rate and median change rate of the DGPS observation value and the previous DGPS observation value, calculate the absolute value of the difference between the observation value change rate and the median change rate, and if the absolute value of the difference exceeds the preset threshold, add the previous DGPS observation value to the negative verification set; Overlapping data in the positive validation set and the negative validation set are identified as gross errors.

7. A submarine node positioning device based on an ultra-short baseline, characterized in that: include: An observation value acquisition module is used to acquire the probe coordinate observation value and the relative coordinate observation value of the first positioning time; wherein the first positioning time is the current time; A solution result acquisition module is used to obtain the node coordinates, node coordinate correction numbers, and variance-covariance matrix of the second positioning time obtained in advance based on the sequential adjustment solution; wherein the second positioning time is the previous positioning time of the first positioning time; The solution module is used to generate an observation vector correction matrix at the first positioning time according to the probe coordinate observation value and the relative coordinate observation value at the first positioning time, and the node coordinate correction number at the second positioning time; generate a gain matrix at the first positioning time according to the variance covariance matrix at the second positioning time; calculate the node coordinate correction number at the first positioning time according to the gain matrix and the observation vector correction matrix at the first positioning time, and the node coordinate correction number at the second positioning time; generate the node coordinates at the first positioning time according to the node coordinates at the second positioning time and the node coordinate correction number at the first positioning time.

8. A computing device, characterized in that include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the seabed node positioning method based on ultra-short baseline as described in any one of claims 1-6.

9. A computer storage medium, characterized in that The storage medium stores at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the seabed node positioning method based on ultra-short baseline as described in any one of claims 1-6.

10. A computer program product, characterized in that It includes at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the seabed node positioning method based on ultra-short baseline as described in any one of claims 1-6.

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