Priori-information-free high-precision target emission point estimation method and system and medium

Abstract

The invention provides a priori-information-free high-precision target launching point estimation method and system and a medium. The method comprises the steps that 1, a visual vector sequence of double satellites to a target is obtained; step 2, performing interpolation alignment on the visual vector sequence according to a time sequence; step 3, performing interpolation alignment to obtain visual vector inverted sequence data; step 4, performing reverse fusion processing on the visual vector reverse sequence data to generate a target three-dimensional track point estimation value sequence; 5, selecting a converged target three-dimensional track point estimation value; step 6, performing polynomial fitting on the converged estimated values of the track points to obtain fitting parameters, and further forming a polynomial fitting equation; and step 7, performing reverse trajectory extrapolation by using a polynomial fitting equation until the reverse trajectory is extrapolated to the surface of the earth to obtain an estimated position of the target launching point. The technical problem that the estimation precision of the target launching point is low under the condition that the time of finding the target for the first time by a satellite is late is solved.

Description

Technical Field

[0001] The present invention belongs to the field of on-board information fusion, and in particular, relates to a method, system and medium for high-precision target emission point estimation without prior information based on polynomial fitting correction. Background Art

[0002] When the dual satellites detect the target, if the satellite first discovers the target late, the first discovered target position is far away from the target launch point, making it difficult to accurately predict the target launch point position, resulting in low target launch point estimation accuracy. In order to improve the target launch point estimation accuracy, it is necessary to obtain a model that is more in line with the motion trajectory law of the target active segment and reduce the error of the extrapolated target launch point.

[0003] The journal article "A Ballistic Missile Launch Point Estimation Method Based on Double-layer Third-order Polynomial Fitting" written by Qiu Mingjie, Telecommunication Technology, Vol. 64, No. 2, 2024, discloses a ballistic missile launch point estimation method based on double-layer third-order polynomial fitting. When only radar measurement data is used, the absolute launch time of the missile is estimated by fitting the active phase time-altitude curve of the ballistic missile through a third-order function, so as to obtain the relative launch time of each ballistic trajectory point relative to the absolute launch time, and then the active phase relative time-horizontal displacement is fitted again using the third-order function to obtain the ballistic missile launch point estimation result. This method is aimed at finding the launch point based on radar measurement data, and is not suitable for finding the launch point based on satellite observation data.

[0004] The journal article "Accurate Solution Method of Launch Point Coordinates Based on Iterative Error Compensation" written by Wen Yonglu, Firepower and Command Control, Vol. 46, No. 5, 2021, discloses an atypical geodetic theme correct solution method based on iterative error compensation. This method uses the launch point azimuth to roughly calculate the target point azimuth, and calls the geodetic theme correct solution method to calculate the initial launch point coordinates and the launch point azimuth. The deviation between the known launch point azimuth and the calculated launch point azimuth is used as negative feedback to correct the target point azimuth, and the launch point coordinates are obtained by iterative solution. However, this method uses the prior information of the launch point azimuth. The launch point azimuth needs to be known, that is, the prior information of the launch point azimuth is needed.

[0005] The journal article "Missile launch point location estimation based on radar data" by the author Shao Wenjia, Modern Radar, Vol. 43, No. 7, 2021, discloses a missile launch point location estimation based on radar data. By establishing mathematical models of the active phase and free flight phase of the first and second stage missiles, the feasibility of estimating the missile launch point location based on radar detection data is analyzed. This method is aimed at finding the launch point based on radar data, and is not suitable for finding the launch point based on satellite observation data.

[0006] The journal article "Trajectory Reconstruction and Optimal Estimation of Ballistic Missile Launch Point Position" by Liu Xinjian, General Aerospace Technology, Vol. 2, No. 5, 2018, discloses a trajectory reconstruction and optimal estimation strategy and method. This trajectory reconstruction method does not require completely consistent ballistic missile parameters, as long as they are roughly close, because it is based on the typical trajectory planning method used by ballistic missiles to attack targets, based on dynamics and control simulation, and by optimizing search parameters and Lambert terminal guidance to meet the reentry boundary conditions, so that the mathematical simulation trajectory can approach the actual flight trajectory. As long as the measurement parameters of the incoming target are obtained, this method can obtain an estimate with a high confidence. This method uses the prior information of the target. However, this method requires the measurement parameters of the incoming target, which also requires the prior information of the target. It is impossible for non-cooperative targets to obtain this information.

[0007] The Chinese invention patent with the publication number CN105022035A discloses a device and method for estimating the launch point of a ballistic target based on model correction, including performing reverse tracking filtering on the point trace data measured by radar, and using the Runge-Kutta extrapolation method to calculate the flight trajectory and launch point position of the ballistic missile, and using the model deviation to correct the estimated launch point position. According to the method disclosed in the present invention, an insensitive filtering algorithm based on the ballistic missile motion equation is adopted to achieve high-precision nonlinear filtering, and the calculation amount is moderate, with high cost-effectiveness. The orbit extrapolation calculation is performed by the Runge-Kutta method, which has high numerical accuracy. The launch point position estimation deviation caused by the active segment is removed by the model deviation correction method, which greatly improves the accuracy of the ballistic missile launch point estimation. However, this method uses the prior information of the ballistic target launch point model. This method requires a ballistic missile target launch point model, and also requires prior information of the target. It is impossible for a non-cooperative target to obtain this information.

[0008] Therefore, it is necessary to provide a high-precision target emission point estimation method without prior information. Summary of the invention

[0009] In view of the defects in the prior art, the object of the present invention is to provide a method, system and medium for high-precision target emission point estimation without prior information.

[0010] The method involved does not require any target-related parameter information to be known in advance, and improves the target launch point estimation accuracy when the satellite first discovers the target late.

[0011] A high-precision target emission point estimation method without prior information provided by the present invention comprises:

[0012] Step 1: Two satellites detect the space target and obtain the visual vector sequences of the two satellites to the target: and m and n are arbitrary positive integers;

[0013] Step 2, interpolate and align the sequence of visual vectors of the double stars to the target and chronologically;

[0014] Step 3, take the visual vector data at the co - visible moments of the double stars after interpolation alignment, perform time reverse processing, and discard the visual vector data at non - co - visible moments of the double stars, obtaining the reverse visual vector data as and k is an arbitrary positive integer;

[0015] Step 4, perform reverse fusion processing on the reverse visual vector data of the double stars to the target, generating a sequence of estimated values of the target three - dimensional trajectory points R = {r1, …, r k};

[0016] Step 5, select the converged estimated values of the target three - dimensional trajectory points R′ = {r1, …, r l} from the sequence of estimated values of the target three - dimensional trajectory points obtained by reverse fusion processing, where l < k; l is an arbitrary positive integer;

[0017] Step 6, perform polynomial fitting on the converged estimated trajectory points R′ = {r1, …, r l}, l < k to obtain fitting parameters, and then form a polynomial fitting equation;

[0018] Step 7, use the polynomial fitting equation for reverse trajectory extrapolation until it extrapolates to the Earth's surface, obtaining the estimated position of the target launch point Launch = [x, y, z].

[0019] Preferably, in Step 1, the sequence of visual vector data of the double stars to the target is all the detection data of the active section of the double stars to the target.

[0020] Preferably, in Step 2, the interpolation method is the interpolation method.

[0021] Preferably, in Step 3, the co - visible moments of the double stars are the same moment or similar moments of the double stars, less than half of the satellite imaging time interval.

[0022] Preferably, in Step 4, the fusion processing uses the line - of - sight intersection positioning method and the extended Kalman filtering algorithm; the line - of - sight intersection positioning method is used to obtain the initial value of the target, and the extended Kalman filtering algorithm is used to obtain the estimated value of the non - initial target point.

[0023] Preferably, in Step 5, the condition for the convergence of the estimated values of the target three - dimensional trajectory points is that the double stars are co - visible for 30 s.

[0024] Preferably, in Step 6, the polynomial fitting method uses the fourth - order polynomial fitting method.

[0025] Preferably, in step 7, the altitude of the earth's surface is obtained from the digital elevation model.

[0026] A high-precision target launch point estimation system without prior information includes:

[0027] Module M1, used for two satellites to detect a space target, and the obtained visual vector sequences of the double stars for the target are respectively and

[0028] Module M2, used for interpolating and aligning the visual vector sequences and of the double stars for the target in chronological order;

[0029] Module M3, used for performing time reverse processing on the visual vector data at the co-visual moment of the double stars after interpolation alignment, discarding the visual vector data at non-co-visual moments of the double stars, and obtaining the reverse visual vector data as respectively and

[0030] Module M4, used for performing reverse fusion processing on the reverse visual vector data of the double stars for the target, and generating a sequence of estimated values of the target three-dimensional trajectory points R = {r1,..., r k};

[0031] Module M5, used for selecting the converged estimated values of the target three-dimensional trajectory points R' = {r1,..., r l}, l < k from the sequence of estimated values of the target three-dimensional trajectory points obtained by reverse fusion processing;

[0032] Module M6, used for performing polynomial fitting on the converged trajectory point estimated values R' = {r1,..., r l}, l < k to obtain fitting parameters, and further forming a polynomial fitting equation;

[0033] Module M7, used for performing reverse trajectory extrapolation using the polynomial fitting equation until it extrapolates to the earth's surface, and obtaining the estimated position of the target launch point Launch = [x, y, z].

[0034] A computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the steps of the method for estimating a high-precision target launch point without prior information.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. By providing a method for estimating a high-precision target launch point without prior information, it is applicable to estimating the target launch point when the satellite first discovers the target relatively late.

[0037] 2. By constructing a polynomial fitting equation that is more consistent with the target's active segment front-end motion trajectory, the target launch point estimation accuracy is improved when the target launch point is extrapolated;

[0038] 3. By providing a high-precision target emission point estimation method without prior information, there is no need to know any target-related parameter information in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0040] Figure 1 A flowchart of a method for estimating a high-precision target emission point without prior information;

[0041] Figure 2 This is the target scene diagram for binary star observation. DETAILED DESCRIPTION

[0042] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0043] The present application provides a method, system and medium for high-precision target emission point estimation without prior information.

[0044] This embodiment provides a high-precision target emission point estimation method without prior information. Figure 1 The flowchart in includes the following steps:

[0045] Step 1: Two satellites detect the space target and obtain the visual vector sequences of the two satellites to the target: and m and n are any positive integers;

[0046] The data sequence of the line-of-sight vector of the binary satellite to the target is all the detection data of the binary satellite to the target in the active phase.

[0047] Step 2: The sequence of the binary star’s view vectors to the target and Interpolate alignment in chronological order;

[0048] The interpolation method is interpolation.

[0049] Step 3: Take the view vector data at the time of common view of the binary star after interpolation alignment and perform time reverse processing, discard the view vector data at the time of non-common view of the binary star, and obtain the view vector reverse order data respectively: and k is any positive integer;

[0050] The double-star co-visual moment is the same moment or a similar moment of the double stars, and is less than half of the satellite imaging time interval.

[0051] Step 4, the double stars perform reverse fusion processing on the reverse-order data of the visual vectors of the target to generate a sequence of estimated values of the target three-dimensional trajectory points R = {r1, …, r k};

[0052] The fusion processing uses the line-of-sight intersection positioning method and the extended Kalman filter algorithm, that is, the EKF algorithm. The line-of-sight intersection positioning method is used to obtain the initial value of the target, and the EKF algorithm is used to obtain the estimated value of the non-initial target point.

[0053] The essence of the line-of-sight intersection positioning method is to solve the intersection point of two lines of sight. Actually, due to the existence of measurement errors, the two lines of sight in space are generally skew lines, so the solution of the target position is transformed into finding the midpoint of the common perpendicular line segment of the two lines of sight. The geometric interpretation is to make a plane through the connection line between the satellites. The plane is located in the middle of the two line-of-sight vectors, that is, the angles between the line-of-sight vectors and the plane are the same, and the intersection point of the projections of the two line-of-sight vectors on the plane is the least squares estimated value of the satellite position.

[0054] The EKF algorithm expands the state equation and the measurement equation by Taylor series to linearize them, and then applies the standard Kalman filter method, that is, the KF method. First, time prediction is performed to obtain the prediction of the state and covariance, and then the prediction value is corrected by the single-star visual vector at the current moment to obtain the estimated value of the target point at the current moment.

[0055] Step 5, select the converged estimated values of the target three-dimensional trajectory points R′ = {r1, …, r l}, l < k from the sequence of estimated values of the target three-dimensional trajectory points obtained by the reverse fusion processing; l is any positive integer;

[0056] The condition for the convergence of the estimated values of the target three-dimensional trajectory points is that the double stars are co-visual for 30 s.

[0057] Step 6, perform polynomial fitting on the converged estimated values of the trajectory points R′ = {r1, …, r l}, l < k to obtain the fitting parameters, and then form a polynomial fitting equation;

[0058] The polynomial fitting method uses the fourth-order polynomial fitting method.

[0059] Step 7, use the polynomial fitting equation to perform reverse trajectory extrapolation until it is extrapolated to the Earth's surface to obtain the estimated position of the target launch point Launch = [x, y, z].

[0060] The altitude of the Earth's surface is obtained from the digital elevation model, that is, DEM.

[0061] This embodiment is further described below in conjunction with the accompanying drawings. This embodiment meets the requirement of high-precision target launch point estimation without prior information when the satellite first discovers the target late.

[0062] See also Figure 1 and Figure 2 , see the following description for details:

[0063] The scene in this embodiment is as follows Figure 2 As shown in the figure, point A, point B and point I are the positions of star A, star B and target I in the geoinertial coordinate system O-XYZ at a certain moment, respectively. Star A and star B observe target I. Simulation target parameters: range is 2180km, maximum flight altitude is 429km, and flight time is 850s. Test conditions are: the satellite discovers the target 50s after the target is launched, the time for the two stars to see the target together is 60s, the sampling period is 1s, and the single star line of sight measurement accuracy is 40μrad (1σ). The target launch point is simulated 100 times by Monte Carlo using the high-precision target launch point estimation method without prior information, and the root mean square error of the target launch point position is 12.742km.

[0064] From the above, we can see that when the satellite first discovers the target late, the error of estimating the target launch point using the high-precision target launch point estimation method without prior information is small.

[0065] The present invention also provides a high-precision target emission point estimation system without prior information, which can be implemented by executing the process steps of the high-precision target emission point estimation method without prior information, that is, those skilled in the art can understand the high-precision target emission point estimation method without prior information as a preferred implementation of the high-precision target emission point estimation system without prior information. Specifically, it includes:

[0066] Module M1 is used for two satellites to detect space targets, and the visual vector sequences of the two satellites to the target are: and

[0067] Module M2, for the binary star-to-target sight vector sequence and Interpolate alignment in chronological order;

[0068] Module M3 is used to take the visual vector data of the binary star common view moment after interpolation alignment and perform time reverse processing, discard the visual vector data of the non-binary star common view moment, and obtain the visual vector reverse order data respectively: and

[0069] Module M4 is used to perform reverse fusion processing on the reverse-order data of the visual vectors of the double stars for the target, and generate a sequence of estimated values of the target three-dimensional trajectory points \(R = \{r_1,\ldots,r\}\). k}

[0070] Module M5 is used to select the estimated values of the target three-dimensional trajectory points \(R'=\{r_1,\ldots,r\}\), \(l < k\) after convergence from the sequence of estimated values of the target three-dimensional trajectory points obtained by the reverse fusion processing. l}, \(l < k\);

[0071] Module M6 is used to perform polynomial fitting on the estimated values of the converged trajectory points \(R'=\{r_1,\ldots,r\}\), \(l < k\) to obtain fitting parameters, and further form a polynomial fitting equation. l}, \(l < k\) to obtain fitting parameters, and further form a polynomial fitting equation;

[0072] Module M7 is used to perform reverse trajectory extrapolation using the polynomial fitting equation until it extrapolates to the Earth's surface to obtain the estimated position of the target launch point Launch = [x, y, z].

[0073] The present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the steps of the method for estimating the target launch point with high precision without prior information.

[0074] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program codes, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a kind of hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or structures within the hardware component.

[0075] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A high-precision target emission point estimation method without prior information, characterized in that: include: Step 1: Two satellites detect the space target and obtain the visual vector sequences of the two satellites to the target: and m and n are any positive integers; Step 2: The sequence of the binary star’s view vectors to the target and Interpolate alignment in chronological order; Step 3: Take the view vector data at the time of common view of the binary star after interpolation alignment and perform time reverse processing, discard the view vector data at the time of non-common view of the binary star, and obtain the view vector reverse order data respectively: and k is any positive integer; Step 4: The dual satellite performs reverse fusion processing on the reverse sequence data of the target’s visual vector to generate a target three-dimensional trajectory point estimation value sequence R = {r1,…,r k }; Step 5, select the estimated value R' = {r1, …, r l} of the target three-dimensional trajectory point after convergence from the sequence of estimated values of the target three-dimensional trajectory points obtained by the reverse fusion process, where l < k; l is any positive integer; Step 6. Perform polynomial fitting on the estimated values \(R'=\{r_1,\ldots,r\) l} of the trajectory points after convergence, where \(l < k\), to obtain fitting parameters, and further form a polynomial fitting equation; Step 7, use the polynomial fitting equation to perform reverse trajectory extrapolation until it is extrapolated to the surface of the earth, and obtain the estimated position of the target launch point Launch = [x, y, z].

2. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In step 1, the visual vector data sequence of the dual-satellite to target is all the detection data of the dual-satellite to target active segment.

3. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In the step 2, the interpolation method is an interpolation method.

4. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In step 3, the time when the two stars are viewed together is the same time or a similar time when the two stars are viewed together, which is less than half of the satellite imaging time interval.

5. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In step 4, the fusion process adopts the line of sight cross positioning method and the extended Kalman filter algorithm; the line of sight cross positioning method is used to obtain the initial value of the target, and the extended Kalman filter algorithm is used to obtain the estimated value of the non-initial target point.

6. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In step 5, the condition for the convergence of the target three-dimensional trajectory point estimation value is that the two stars are in common view for 30 seconds.

7. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In step 6, the polynomial fitting method adopts a fourth-order polynomial fitting method.

8. The high-precision target emission point estimation method without prior information according to claim 1 is characterized in that: In step 7, the altitude of the earth's surface is obtained from a digital elevation model.

9. A high-precision target emission point estimation system without prior information, characterized in that: include: Module M1 is used for two satellites to detect space targets, and the visual vector sequences of the two satellites to the target are: and Module M2, for the binary star-to-target sight vector sequence and Interpolate alignment in chronological order; Module M3 is used to take the visual vector data of the binary star common view moment after interpolation alignment and perform time reverse processing, discard the visual vector data of the non-binary star common view moment, and obtain the visual vector reverse order data respectively: and Module M4 is used to perform reverse fusion processing on the reverse sequence data of the target’s visual vector of the binary satellite to generate a target three-dimensional trajectory point estimation value sequence R = {r1,…,r k }; Module M5, used to select the converged target three-dimensional trajectory point estimation value R′={r1,…,r l },l <k; Module M6, which is used to perform polynomial fitting on the estimated values of the converged trajectory points \(R'=\{r_1,\ldots,r\) l}\), \(l < k\) to obtain fitting parameters, and further form a polynomial fitting equation; Module M7 is used to perform reverse trajectory extrapolation using a polynomial fitting equation until the trajectory is extrapolated to the surface of the earth to obtain an estimated position of the target launch point Launch = [x, y, z].

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for high-precision target emission point estimation without prior information described in any one of claims 1 to 8 are implemented.

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