Fusion positioning method and device of cross coarse estimation and iterative fine solution, and medium

Abstract

The invention discloses a fusion positioning method and device of cross coarse estimation and iterative fine solution, and a medium. The method comprises the following steps: obtaining a direction finding result in a multi-measurement-station scene; performing cross positioning by using the direction finding result to obtain a geometric figure formed by cross positioning; calculating the gravity center of a geometric figure formed by cross positioning, and carrying out rough estimation on the position of a target radiation source; taking a coarse positioning result as an initial value, and gradually correcting an error through a nonlinear optimization iterative algorithm to obtain a real coordinate of the position of the target radiation source; optimizing the real coordinates of the target radiation source through an iteration method; and obtaining a final positioning result. Cross positioning is carried out on a target by using a direction finding result, rough estimation of a target position can be realized for a target position geometric figure formed by multiple stations by adopting a mode of taking a gravity center, finally, accurate positioning of the target is carried out by adopting iterative fine calculation, and effective combination of cross rough estimation and iterative fine calculation is adopted to realize accurate positioning of the target. The balance between the precision and the real-time performance of target positioning is solved, the flexibility is high, and the practicability is high.

Description

Technical Field

[0001] The present invention relates to the field of positioning technology, and in particular to a positioning method, device and medium for integrating cross-coarse estimation with iterative precise solution. Background Art

[0002] In the increasingly complex airspace of electromagnetic environment, higher and newer requirements are put forward for target positioning algorithms. However, for different application environments, it is urgently necessary to design target positioning around the balance of "accuracy-real-time-robustness". The design and engineering implementation of a positioning method based on the combination of cross-coarse estimation and iterative fine solution is of great significance.

[0003] Among the existing technologies, the current positioning technology still has deficiencies in terms of accuracy, real-time performance, and robustness. Conventional single positioning methods are difficult to meet demanding application scenarios with positioning accuracy requirements. For example, cross-positioning accuracy depends on direction-finding accuracy. There are few technical studies on the combination of cross-rough estimation and iterative fine solution positioning technology. In particular, the geometric center of gravity of cross-positioning is used as the initial value of the iterative algorithm, which makes it difficult to ensure accuracy and iterative convergence speed, and cannot solve the problem of high-precision positioning of the target. It has high flexibility and strong practicality. Summary of the Invention

[0004] The technical problem to be solved by the present invention is that positioning technology has deficiencies in terms of accuracy, real-time performance, and robustness. The purpose is to provide a fusion positioning method, equipment, and medium of cross-coarse estimation and iterative fine solution. By using the direction finding results to cross-locate the target, the target position geometry formed by multiple stations can be roughly estimated by taking the center of gravity. Finally, iterative fine solution is used to accurately locate the target. The effective combination of cross-coarse estimation and iterative fine solution solves the balance between the accuracy and real-time performance of target positioning, and has high flexibility and strong practicality.

[0005] The present invention is achieved through the following technical solutions:

[0006] The first aspect of the present invention provides a fusion positioning method of cross-coarse estimation and iterative fine solution, comprising the following specific steps:

[0007] Obtain direction finding results in multi-station scenarios;

[0008] Performing cross-positioning using the direction finding results to obtain a geometric figure formed by the cross-positioning;

[0009] Calculate the center of gravity of the geometric figure formed by cross positioning and make a rough estimate of the target radiation source position;

[0010] Using the coarse positioning result as the initial value, the error is gradually corrected through a nonlinear optimization iterative algorithm to obtain the true coordinates of the target radiation source position;

[0011] Optimizing the true coordinates of the target radiation source by an iterative method;

[0012] Determine whether the positioning accuracy of the real coordinates of the optimized target radiation source reaches the preset threshold; if the positioning accuracy reaches the preset threshold, end the iteration and obtain the final positioning result.

[0013] Furthermore, the obtaining of direction-finding results in a multi-measurement station scenario further includes performing coordinate system conversion on the direction-finding results obtained in the multi-measurement station scenario, and the conversion process includes:

[0014]

[0015] Where B represents latitude, L represents longitude, H represents altitude, N represents the radius of curvature of a point on the ellipsoid, and e represents the first eccentricity of the ellipsoid.

[0016] Furthermore, the target position geometry formed by cross-positioning is obtained, specifically including:

[0017] Select at least three measurement stations and extract the coordinates (xi,yi) of each measurement station, where i represents the number of the measurement station;

[0018] According to the direction finding results, obtain the measurement direction lines of at least three measurement stations;

[0019] Obtain the intersection of multiple measurement direction lines and enclose the target position geometry formed by cross positioning.

[0020] Furthermore, the calculation of the center of gravity of the target radiation source geometric figure formed by the cross positioning to perform a rough estimation of the target position specifically includes:

[0021] Get the endpoints of the target position geometry and get the rough estimate of the target radiation source position T'(x T ,y T ),in,

[0022] Furthermore, the coarse positioning result is used as the initial value, and the error is gradually corrected through a nonlinear optimization iterative algorithm to obtain the true coordinates of the target radiation source position, specifically including:

[0023] Obtaining the initial reference coordinates of the target radiation source and its distance measurements from at least three measurement stations to obtain a distance function;

[0024] Based on Taylor expansion, the distance function is linearly approximated and the distance variable equation is established;

[0025] Calculate the offset between the roughly estimated position of the target radiation source and the reference coordinates;

[0026] Based on the distance variable equation, construct a system of linear equations and solve for the offset;

[0027] The real coordinates of the target radiation source are obtained according to the offset.

[0028] Furthermore, the distance function construction process includes:

[0029]

[0030] Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate to the real coordinate of the target radiation source, ρ j represents the distance measurement from T to the jth known reference point, (x j ,y j ) represents the coordinates of the jth known reference point.

[0031] Furthermore, the process of constructing the distance variable equation includes:

[0032]

[0033] Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate to the real coordinate of the target radiation source, ρ j represents the distance measurement value from the target radiation source to the jth known reference point, represents the reference measurement value from the target radiation source to the jth known reference point, (x j ,y j ) represents the coordinates of the jth known reference point, a xj and a yj Represents the coefficient calculated based on the reference point and true coordinates of the target radiation source and the distance between them, Δρ j Represents the distance error from the target radiation source to the jth known reference point.

[0034] Furthermore, the process of obtaining the real coordinates of the target radiation source according to the offset includes:

[0035]

[0036] ΔX=H -1 Δρ

[0037]

[0038] Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate of the target radiation source to the real coordinate, a xj and a yj Represents the coefficient calculated based on the reference point and true coordinates of the target radiation source and the distance between them, Δρ j represents the distance error from the target radiation source to the jth known reference point, Δρ represents the distance error from the target radiation source to all known reference points, H represents the position matrix, which contains the position information of the target radiation source relative to each reference point and is used to convert the distance error into the coordinate adjustment amount, and ΔX represents the coordinate adjustment amount of the target radiation source.

[0039] A second aspect of the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a fusion positioning method of cross-coarse estimation and iterative fine solution is implemented.

[0040] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a fusion positioning method of cross-coarse estimation and iterative fine solution.

[0041] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0042] 1. The present invention first obtains the geodetic coordinates of the measurement site and converts them into rectangular space coordinates. The direction-finding results are then used to cross-locate the target. The target position geometry formed by multiple stations can be roughly estimated by taking the center of gravity. Finally, an iterative fine solution is used to accurately locate the target, thus achieving a balance between target positioning accuracy and real-time performance.

[0043] 2. The present invention utilizes a positioning algorithm based on the combination of cross-coarse estimation and iterative fine solution in the fields of electronic countermeasures and UAV clusters, adopts the geometric intersection method, and utilizes the geometric relationship of at least three non-collinear measurement points to perform a rough estimation of the target position. Through a "coarse-fine" two-stage design, efficient and high-precision target positioning is achieved in complex environments. It is one of the key technologies in the fields of autonomous driving, robotics, the Internet of Things, and low-altitude economy. It can adapt to more application scenarios and can produce greater effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the examples. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. In the drawings:

[0045] Figure 1 This is the multi-point positioning scenario process in an embodiment of the present invention;

[0046] Figure 2 This is the single point positioning scenario process in an embodiment of the present invention;

[0047] Figure 3 Schematic diagram of dual-station cross positioning in an embodiment of the present invention;

[0048] Figure 4 Schematic diagram of three-station cross-positioning in an embodiment of the present invention;

[0049] Figure 5 Schematic diagram of initial value calculation using the rough estimated centroid method for multiple measurement stations in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0051] As a possible implementation, Figure 1 and Figure 2 As shown, this embodiment provides a fusion positioning method of cross-coarse estimation and iterative fine solution. The basic principle of the design method of this embodiment is to first perform coordinate conversion based on the direction-finding result information of the target and the position information of the measuring station to complete the rectangular space coordinates of the measuring station. Secondly, a geometric figure of the initial position of the target is formed through a cross-positioning algorithm. The geometric center of gravity of the geometric figure is taken as the coarse estimation result, and it is brought into the initial value of the iterative method to quickly and accurately locate the target.

[0052] In some possible implementations, this embodiment mainly includes the following key steps, which are as follows:

[0053] Obtain direction finding results in multi-station scenarios;

[0054] Performing cross-positioning using the direction finding results to obtain a geometric figure formed by the cross-positioning;

[0055] Calculate the center of gravity of the geometric figure formed by cross positioning and make a rough estimate of the target radiation source position;

[0056] Using the coarse positioning result as the initial value, the error is gradually corrected through a nonlinear optimization iterative algorithm to obtain the true coordinates of the target radiation source position;

[0057] Optimizing the true coordinates of the target radiation source by an iterative method;

[0058] Determine whether the positioning accuracy of the real coordinates of the optimized target radiation source reaches the preset threshold; if the positioning accuracy reaches the preset threshold, end the iteration and obtain the final positioning result.

[0059] In this embodiment, the basic principle is to first obtain the geodetic coordinates of the measurement stations and convert them into rectangular space coordinates. The direction-finding results are then used to cross-locate the target. The target position geometry formed by multiple stations can be roughly estimated by taking the center of gravity. Finally, an iterative refinement algorithm is used to accurately locate the target, thus achieving a balance between target positioning accuracy and real-time performance. A rough estimation approach and mechanism using the cross-centroid method of multiple measurement stations is adopted. The cross-rough estimation results are used as initial values for iterative processing to further improve positioning accuracy. This algorithm balances iterative convergence speed and positioning accuracy. The multiple measurement stations can be fixed stations or a single measurement device on an aircraft, vehicle, or ship, reading direction-finding results along a specific motion trajectory, i.e., a position selection approach based on multiple measurements. Furthermore, this embodiment supports single-station positioning applications using coarse estimation and iterative refinement of multiple measurements from a single station. The combined cross-positioning and iterative positioning approach of this embodiment reduces the limitations of a single positioning approach and improves positioning accuracy and reliability.

[0060] In some possible implementations, since the input data are the geodetic coordinates of the measurement station, and the coordinate data used in solving the positioning equation combining cross-coarse estimation and iterative fine solution are rectangular space coordinates, it is necessary to implement a coordinate system conversion.

[0061] Constants used in the operation:

[0062] Convert geodetic coordinates to rectangular space coordinates:

[0063] make

[0064] Therefore, the process of obtaining direction-finding results and performing coordinate system conversion in a multi-station scenario includes:

[0065]

[0066] Among them, B represents latitude, L represents longitude, H represents altitude, and N represents the radius of curvature of a point on the ellipsoid.

[0067] In some possible implementations, in order to simplify the calculation and better illustrate the core idea of the algorithm, it is assumed that on a two-dimensional plane, the direction of the line connecting the two stations is taken as the X axis, and the midpoint of the two stations is taken as the origin O. The cross-positioning diagram of the dual-station direction finding is as follows: Figure 3 shown.

[0068] A and B are two measurement stations, and T is the target radiation source. The positions of each point have been converted from geodetic coordinates to rectangular coordinates, which can be expressed as follows: the coordinates of measurement station A are (x1, y1), the coordinates of measurement station B are (x2, y2), and the coordinates of target T are (xT, yT). The azimuths from target T to the two measurement stations are α1 and α2.

[0069] According to the point-slope form, the expressions of the following two straight lines are as follows:

[0070] L1:y-y1=tanα1(x-x1)

[0071] L2:y-y2=tanα2(x-x2)

[0072] The intersection point of the two lines (x T ,y T ) into the linear expression and sort it out to get the following system of equations:

[0073]

[0074] Solving formula 1, we can get the position of the target radiation source as:

[0075]

[0076] Formula 2 shows that according to the principle of dual-station direction finding cross positioning, in order to estimate the position coordinates of the target radiation source, since the positions of the two measuring stations are fixed, a coordinate system is established according to their geographical locations. The coordinate positions (x1, y1) and (x2, y2) of the two stations and the azimuths α1 and α2 from the target radiation source to the two measuring stations can be known, and the position coordinates (xT, yT) of the target radiation source can be obtained. However, in real application scenarios, due to the existence of direction finding errors, the azimuth measured by a single measuring station will deviate from the true value, resulting in a large deviation between the position of the target radiation source measured by the dual stations and the true value. Therefore, the following method can be used: Figure 4 The three stations shown are cross-located to the target emitter.

[0077] In some possible implementations, obtaining a target position geometry formed by cross-positioning specifically includes:

[0078] Select at least three measuring stations and extract the coordinates (xi, yi) of each measuring station, where i represents the number of the measuring station; that is, by selecting appropriate measuring stations A, B, and C, whose coordinates are (x1, y1), (x2, y2), and (x3, y3), respectively, for the selected station positions, multiple station positions obtained by moving a single measuring station can also be applied to single-station positioning;

[0079] Obtain the intersection of multiple measurement direction lines and enclose the target position geometry formed by cross positioning, such as Figure 4 As shown, the area enclosed by the triangle DEF is the area where the measured target radiation source T' is located. Then the center of gravity of the target radiation source geometric figure formed by the cross positioning is calculated to make a rough estimate of the target position, as shown in Figure 5 As shown, specifically including:

[0080] Get the endpoint of the target position geometry, that is, the coordinates of point DEF, and get the rough estimate of the target radiation source position T'(x T ,y T ),in, In this embodiment, n=3, then

[0081]

[0082] In some possible implementations, the coarse positioning result is used as the initial value, and the error is gradually corrected through a nonlinear optimization iterative algorithm to obtain the true coordinates of the target radiation source position, specifically including:

[0083] Obtaining the initial reference coordinates of the target radiation source and its distance measurements from at least three measurement stations to obtain a distance function;

[0084] Based on Taylor expansion, the distance function is linearly approximated and the distance variable equation is established;

[0085] Calculate the offset between the roughly estimated position of the target radiation source and the reference coordinates;

[0086] Based on the distance variable equation, construct a system of linear equations and solve for the offset;

[0087] The real coordinates of the target radiation source are obtained according to the offset.

[0088] In some possible implementations, the specific calculation process is:

[0089] The distances between the target position and the measuring stations A, B, and C are measured and recorded as: ρ1, ρ2, ρ3. The approximate positions of each member in the network in geodetic coordinates are recorded as: A(x1, y1), B(x2, y2), C(x3, y3), The distance measurement module can give the distance between T and A, B, and C as:

[0090] Assume that the real coordinates of T are: (x u ,y u ), and its relationship with the reference point is:

[0091]

[0092] According to Taylor's formula:

[0093]

[0094]

[0095] Based on the above content, select any two groups to solve as follows:

[0096]

[0097] Then we get:

[0098] ΔX=H -1 Δρ

[0099]

[0100] Formula 3 is iterated multiple times to determine whether further iteration is needed based on the size of the error ΔX. If the error exceeds the threshold, the positioning result is substituted into the original formula and the iterative process is repeated to eventually approach the true position.

[0101] Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate to the real coordinate of the target radiation source, ρ j represents the distance measurement value from the target radiation source to the jth known reference point, represents the reference measurement value from the target radiation source to the jth known reference point, (x j ,y j ) represents the coordinates of the jth known reference point, a xj and a yj Represents the coefficient calculated based on the reference point and true coordinates of the target radiation source and the distance between them, Δρ j represents the distance error from the target radiation source to the jth known reference point, Δρ represents the distance error from the target radiation source to all known reference points, H represents the position matrix, which contains the position information of the target radiation source relative to each reference point and is used to convert the distance error into the coordinate adjustment amount, and ΔX represents the coordinate adjustment amount of the target radiation source.

[0102] As a possible implementation, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the program, a fusion positioning method of cross-coarse estimation and iterative fine solution is implemented.

[0103] As a possible implementation, this embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a fusion positioning method of cross-coarse estimation and iterative fine solution is implemented.

[0104] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fusion positioning method of cross-coarse estimation and iterative fine solution, characterized by: The specific steps include: Obtain direction finding results in multi-station scenarios; Performing cross-positioning using the direction finding results to obtain a geometric figure formed by the cross-positioning; Calculate the center of gravity of the geometric figure formed by cross positioning and make a rough estimate of the target radiation source position; Using the coarse positioning result as the initial value, the error is gradually corrected through a nonlinear optimization iterative algorithm to obtain the true coordinates of the target radiation source position; Optimizing the true coordinates of the target radiation source by an iterative method; Determine whether the positioning accuracy of the real coordinates of the optimized target radiation source reaches a preset threshold; If the positioning accuracy reaches the preset threshold, the iteration ends and the final positioning result is obtained.

2. The fusion positioning method of cross-coarse estimation and iterative fine solution according to claim 1 is characterized in that: The step of obtaining direction-finding results in a multi-measurement station scenario further includes performing coordinate system conversion on the direction-finding results obtained in the multi-measurement station scenario. The conversion process includes: Where B represents latitude, L represents longitude, H represents altitude, N represents the radius of curvature of a point on the ellipsoid, and e represents the first eccentricity of the ellipsoid.

3. The fusion positioning method of cross-coarse estimation and iterative fine solution according to claim 1 is characterized in that: The target position geometry formed by cross-positioning is obtained, specifically including: Select at least three measurement stations and extract the coordinates (xi,yi) of each measurement station, where i represents the number of the measurement station; According to the direction finding results, obtain the measurement direction lines of at least three measurement stations; Obtain the intersection of multiple measurement direction lines and enclose the target position geometry formed by cross positioning.

4. The fusion positioning method of cross-coarse estimation and iterative fine solution according to claim 1 is characterized in that: The calculation of the center of gravity of the target radiation source geometric figure formed by the cross positioning to perform a rough estimation of the target position specifically includes: Get the endpoints of the target position geometry and get the rough estimate of the target radiation source position T'(x T, y T ),in, 5. The fusion positioning method of cross-coarse estimation and iterative fine solution according to claim 1 is characterized in that: The method uses the rough positioning result as the initial value and gradually corrects the error through a nonlinear optimization iterative algorithm to obtain the true coordinates of the target radiation source position, specifically including: Obtaining the initial reference coordinates of the target radiation source and its distance measurements from at least three measurement stations to obtain a distance function; Based on Taylor expansion, the distance function is linearly approximated and the distance variable equation is established; Calculate the offset between the roughly estimated position of the target radiation source and the reference coordinates; Based on the distance variable equation, construct a system of linear equations and solve for the offset; The real coordinates of the target radiation source are obtained according to the offset.

6. The fusion positioning method of cross-coarse estimation and iterative precise solution according to claim 5 is characterized in that: The distance function construction process includes: Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate to the real coordinate of the target radiation source, ρ j represents the distance measurement from T to the jth known reference point, (x j ,y j ) represents the coordinates of the jth known reference point.

7. The fusion positioning method of cross-coarse estimation and iterative fine solution according to claim 5 is characterized in that: The process of constructing the distance variable equation includes: Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate to the real coordinate of the target radiation source, ρ j represents the distance measurement value from the target radiation source to the jth known reference point, represents the reference measurement value from the target radiation source to the jth known reference point, (x j ,y j ) represents the coordinates of the jth known reference point, a xj and a yj Represents the coefficient calculated based on the reference point and true coordinates of the target radiation source and the distance between them, Δρ j Represents the distance error from the target radiation source to the jth known reference point.

8. The fusion positioning method of cross-coarse estimation and iterative fine solution according to claim 5 is characterized in that: The process of obtaining the real coordinates of the target radiation source according to the offset includes: ΔX=H -1 Dr. Among them, (x u ,y u ) represents the real coordinates of the target radiation source, represents the reference coordinates of the target radiation source, (Δx u ,Δy u ) represents the adjustment amount from the reference value coordinate of the target radiation source to the real coordinate, a xj and a yj Represents the coefficient calculated based on the reference point and true coordinates of the target radiation source and the distance between them, Δρ j represents the distance error from the target radiation source to the jth known reference point, Δρ represents the distance error from the target radiation source to all known reference points, H represents the position matrix, which contains the position information of the target radiation source relative to each reference point and is used to convert the distance error into the coordinate adjustment amount, and ΔX represents the coordinate adjustment amount of the target radiation source.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the fusion positioning method of cross-coarse estimation and iterative fine solution as described in any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the fusion positioning method of cross-coarse estimation and iterative fine solution as described in any one of claims 1 to 8 is implemented.

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