Target state estimation method based on attitude correction-robust fusion

Abstract

The invention belongs to the technical field of target state estimation, and discloses a target state estimation method based on attitude correction-robust fusion, and the method comprises the steps: obtaining data, including the observation information of an air platform for a maritime cooperation platform and a target, the attitude information of the air platform, and the position information of the air platform and the cooperation platform; calculating to obtain correction postures of the air platforms F1 and F2; and the corrected attitude and the robust algorithm model are fused to realize accurate tracking of the target. According to the method, attitude correction and a robust algorithm are fused, and errors of a sensor observation system and an attitude angle system are reduced at the same time; and an interactive multi-model is introduced to realize maneuvering target state estimation under system errors.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the technical field of target state estimation, and in particular relates to a target state estimation method based on attitude correction-anti-error fusion. Background Art

[0002] Target state estimation is an important research branch in the field of automatic control, statistical signal processing and information fusion. It is widely used in engineering applications such as navigation and positioning, target tracking, signal processing, communication, control, robotics and space exploration. State estimation theory aims to accurately estimate the state variables such as target position, velocity and acceleration from a series of observation data. In the linear state space model with Gaussian distribution noise, Kalman filtering is a classic state estimation method; in the nonlinear state space model with thick-tailed non-Gaussian distribution noise and thick-tailed skewed non-Gaussian distribution noise, high-order difference cubature Kalman filter, Gaussian approximation filter based on quadrature point propagation and particle filter and other high-precision state estimation methods have been proposed successively. In addition, in the problem of multi-target state estimation, methods based on random set framework such as probability hypothesis density filtering algorithm and multi-Bernoulli filtering play an important role.

[0003] In the process of target state estimation, the sensor observation system error and platform attitude system error will have a great impact on the state estimation accuracy and track association of the whole process, so it is necessary to reduce the system error.

[0004] Zhu Huimin et al. (Zhu Huimin, Jia Zhengrong, Wang Hangyu, et al. UAV target positioning method for different field of view auxiliary beacons [J]. Journal of National University of Defense Technology, 2019, 41(03): 125-136.) proposed an attitude angle fusion estimation method to solve the problem that the attitude angle error has a great influence on the UAV target state estimation, but only considered the influence of the attitude angle error. Cui Yaqi et al. (Cui Yaqi, Xiong Wei, He You. Robust tracking algorithm for ground-to-air coordinated air defense targets [J]. Acta Aeronautica Sinica, 2014, 35(04): 1079-1090.) proposed a robust algorithm to solve the target state estimation method under the existence of system errors in the airborne radar and ground-based radar coordinated air defense early warning system, but only considered the influence of the sensor observation system error. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a target state estimation method based on attitude correction-anti-error fusion.

[0006] The present invention is implemented in this way: a target state estimation method based on attitude correction-anti-error fusion, the method comprising:

[0007] S1: Acquisition of data, including observation information of the aerial platform on the maritime cooperation platform and targets, aerial platform attitude information, and location information of the aerial platform and cooperation platform;

[0008] S2: Calculate the corrected attitudes of the aerial platforms F1 and F2;

[0009] S3: The corrected posture is integrated with the robust algorithm model to achieve accurate tracking of the target.

[0010] Further, the S1 specifically includes:

[0011] Define the observation values ​​of aerial platforms F1 and F2 on sea target T The observed true value Observation system error and observational random error The following relationship exists:

[0012]

[0013] in, are the true values ​​of the observed distance, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2 respectively; They are the observation range, azimuth and elevation system errors of the aerial platforms F1 and F2 to the sea target T; are the random errors of the observation distance, azimuth and elevation angle of the aerial platforms F1 and F2 to the sea target T;

[0014] Define the observation values ​​of aerial platforms F1 and F2 on the sea cooperation platform C The observed true value Observation system error and observational random error The following relationship exists:

[0015]

[0016] in, They are the true values ​​of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the offshore cooperation platform C; They are the observation distance, azimuth and pitch angle system errors of the aerial platforms F1 and F2 to the offshore cooperation platform C; are the random errors of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the offshore cooperation platform C;

[0017] Define the attitude measurements of the aerial platforms F1 and F2 and attitude truth Attitude system error and attitude random error The following relationship exists:

[0018]

[0019] in, are the true values ​​of the yaw angle, pitch angle, and roll angle of the aerial platforms F1 and F2 respectively; They are the yaw angle, pitch angle, and roll angle system errors of the aerial platforms F1 and F2 respectively; They are the random errors of yaw angle, pitch angle and roll angle of aerial platforms F1 and F2 respectively;

[0020] By simultaneously observing the cooperative platform and the target at sea, the attitude angle is inversely solved using the high-precision position information provided by the cooperative platform in real time, thereby reducing the influence of the sensor observation system error and the attitude angle system error.

[0021] Ideally, the observation information from the air platform to the sea cooperation platform Aerial platform attitude information and aerial platforms and offshore cooperation platform Xg C The position information of the offshore cooperation platform in the earth coordinate system can be obtained as follows:

[0022]

[0023] Further, the S2 specifically includes:

[0024] Due to the observation information of the aerial platform to the maritime cooperation platform and aerial platform attitude information There is an error, the above equation does not hold, and the indicator function is constructed:

[0025]

[0026] Solving and correcting posture Make Track targets at sea using corrected attitude to improve target tracking accuracy;

[0027] According to the above formula, the correction attitudes of the aerial platforms F1 and F2 are obtained respectively:

[0028] Further, the S3 specifically includes:

[0029] Based on the corrected posture, the position information of the target at the fusion center is obtained:

[0030]

[0031] Among them: M1, M2 are system error coefficients; is the systematic error term; W1 and W2 are random errors;

[0032] Let N = [M1 M2] [M1 - M2] T ([M1 -M2] [M1 -M2] T ) -1 ;

[0033] Construct the pseudo-measurement equation:

[0034]

[0035] W f =(E 3×3 -N)W1+(E 3×3 +N)W2

[0036] Among them, the error covariance matrix of W1 is The error covariance matrix of W2 is

[0037] In summary, the formula can be written as:

[0038] Z=2HX+W f

[0039] Where: W f It is approximately zero-mean Gaussian white noise, and its error covariance matrix is:

[0040]

[0041] Another object of the present invention is to provide a target state estimation system based on attitude correction-anti-error fusion based on the target state estimation method based on attitude correction-anti-error fusion, the system specifically comprising:

[0042] A data acquisition module is used to acquire data, including observation information of the aerial platform on the offshore cooperation platform and targets, the aerial platform attitude information, and the location information of the aerial platform and the cooperation platform;

[0043] A correction attitude calculation module is connected to the data acquisition module and is used to calculate the correction attitudes of the aerial platforms F1 and F2;

[0044] The precise tracking module is connected to the correction posture calculation module, and integrates the correction posture with the anti-error algorithm model to achieve precise tracking of the target.

[0045] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the target state estimation method based on attitude correction-anti-error fusion.

[0046] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to perform the steps of the target state estimation method based on attitude correction-anti-error fusion.

[0047] Another object of the present invention is to provide an information data processing terminal, characterized in that the information data processing terminal is used to implement the target state estimation system based on attitude correction-anti-error fusion.

[0048] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0049] (1) Fusion of attitude correction and robustness algorithms to simultaneously reduce the sensor observation system error and attitude angle system error;

[0050] (2) Introduce interacting multiple models to realize the state estimation of maneuvering targets under system errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flow chart of a target state estimation method based on attitude correction-anti-error fusion provided by an embodiment of the present invention;

[0052] Figure 2 It is a structural diagram of a target state estimation system based on attitude correction-anti-error fusion provided by an embodiment of the present invention;

[0053] Figure 3 is a situation comparison diagram provided by an embodiment of the present invention;

[0054] In the figure: 1. Data acquisition module; 2. Correction posture calculation module; 3. Precision tracking module. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0056] like Figure 1 As shown, an embodiment of the present invention provides a target state estimation method based on attitude correction-anti-error fusion, the method comprising:

[0057] S1: Acquisition of data, including observation information of the aerial platform on the maritime cooperation platform and targets, aerial platform attitude information, and location information of the aerial platform and cooperation platform;

[0058] S2: Calculate the corrected attitudes of the aerial platforms F1 and F2;

[0059] S3: The corrected posture is integrated with the robust algorithm model to achieve accurate tracking of the target.

[0060] The S1 specifically includes:

[0061] Define the observation values ​​of aerial platforms F1 and F2 on sea target T The observed true value Observation system error and observational random error The following relationship exists:

[0062]

[0063] in, are the true values ​​of the observed distance, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2 respectively; They are the observation range, azimuth and elevation system errors of the aerial platforms F1 and F2 to the sea target T; are the random errors of the observation distance, azimuth and elevation angle of the aerial platforms F1 and F2 to the sea target T;

[0064] Define the observation values ​​of aerial platforms F1 and F2 on the sea cooperation platform C The observed true value Observation system error and observational random error The following relationship exists:

[0065]

[0066] in, They are the true values ​​of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the offshore cooperation platform C; They are the observation distance, azimuth and pitch angle system errors of the aerial platforms F1 and F2 to the offshore cooperation platform C; are the random errors of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the offshore cooperation platform C;

[0067] Define the attitude measurements of the aerial platforms F1 and F2 and attitude truth Attitude system error and attitude random error The following relationship exists:

[0068]

[0069] in, are the true values ​​of the yaw angle, pitch angle, and roll angle of the aerial platforms F1 and F2 respectively; They are the yaw angle, pitch angle, and roll angle system errors of the aerial platforms F1 and F2 respectively; They are the random errors of yaw angle, pitch angle and roll angle of aerial platforms F1 and F2 respectively;

[0070] By simultaneously observing the cooperative platform and the target at sea, the attitude angle is inversely solved using the high-precision position information provided by the cooperative platform in real time, thereby reducing the influence of the sensor observation system error and the attitude angle system error.

[0071] Ideally, the observation information from the air platform to the sea cooperation platform Aerial platform attitude information and aerial platforms and offshore cooperation platform Xg C The position information of the offshore cooperation platform in the earth coordinate system can be obtained as follows:

[0072]

[0073] The S2 specifically includes:

[0074] Due to the observation information of the aerial platform to the maritime cooperation platform and aerial platform attitude information There is an error, the above equation does not hold, and the indicator function is constructed:

[0075]

[0076] Solving and correcting posture Make Track targets at sea using corrected attitude to improve target tracking accuracy;

[0077] According to the above formula, the correction attitudes of the aerial platforms F1 and F2 are obtained respectively:

[0078] The S3 specifically includes:

[0079] Based on the corrected posture, the position information of the target at the fusion center is obtained:

[0080]

[0081] Among them: M1, M2 are system error coefficients; is the systematic error term; W1 and W2 are random errors;

[0082] Let N = [M1 M2] [M1 - M2] T ([M1 -M2] [M1 -M2] T )-1 ;

[0083] Construct the pseudo-measurement equation:

[0084]

[0085] W f =(E 3×3 -N)W1+(E 3×3 +N)W2

[0086] Among them, the error covariance matrix of W1 is The error covariance matrix of W2 is

[0087] In summary, the formula can be written as:

[0088] Z=2HX+W f

[0089] Where: W f It is approximately zero-mean Gaussian white noise, and its error covariance matrix is:

[0090]

[0091] like Figure 2 As shown, an embodiment of the present invention provides a target state estimation system based on attitude correction-anti-error fusion based on the target state estimation method based on attitude correction-anti-error fusion, and the system specifically includes:

[0092] A data acquisition module is used to acquire data, including observation information of the aerial platform on the offshore cooperation platform and targets, the aerial platform attitude information, and the location information of the aerial platform and the cooperation platform;

[0093] A correction attitude calculation module is connected to the data acquisition module and is used to calculate the correction attitudes of the aerial platforms F1 and F2;

[0094] The precise tracking module is connected to the correction posture calculation module, and integrates the correction posture with the anti-error algorithm model to achieve precise tracking of the target.

[0095] An embodiment of the present invention provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the target state estimation method based on posture correction-anti-error fusion.

[0096] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the target state estimation method based on attitude correction-anti-error fusion.

[0097] An embodiment of the present invention provides an information data processing terminal, which is used to implement the target state estimation system based on attitude correction-anti-error fusion.

[0098] Relevant evidence of the technical effects achieved by the embodiments of the present invention.

[0099] A typical scenario was set for simulation verification. The total simulation time was 200s. The locations of observation platforms 1 and 2 were set to [507.53.5]km and [1283.5]km respectively. The initial position of the cooperation platform was at the fusion center, moving 2000m in the direction of 90° azimuth. The initial position of the target was at a distance of 200km at a azimuth of 0° relative to the fusion center.

[0100] The observation system error of observation platform 1 is [5m 0.06°0.08°], and the random error is [8m 0.12°0.12°]; the observation system error of observation platform 2 is [5m 0.06°0.08°], and the random error is [8m 0.12°0.12°]; the attitude angle system error of observation platform 1 is [0.1°0.1°0.1°], and the random error is [0.2°0.2°0.2°]; the attitude angle system error of observation platform 2 is [0.3°0.3°0.3°], and the random error is [0.2°0.2°0.2°].

[0101] Get the state estimation trajectory diagram of the target, such as Figure 3 As shown in the simulation diagram, it can be seen that the present invention can achieve better state estimation of the target, and the error of the target state estimation at the terminal moment is 14.83m, which proves the effectiveness of the present invention.

[0102] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0103] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A target state estimation method based on attitude correction-anti-error fusion, characterized in that: The method includes: S1: Acquisition of data, including observation information of the aerial platform on the maritime cooperation platform and targets, aerial platform attitude information, and location information of the aerial platform and cooperation platform; S2: Calculate the corrected attitudes of the aerial platforms F1 and F2; S3: The corrected posture is integrated with the robust algorithm model to achieve accurate tracking of the target.

2. The target state estimation method based on attitude correction-anti-error fusion according to claim 1 is characterized in that: The S1 specifically includes: Define the observation values ​​of aerial platforms F1 and F2 on sea target T The observed true value Observation system error and observational random error The following relationship exists: in, They are respectively the true values ​​of the observed distance, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2; They are the observation range, azimuth and elevation system errors of the aerial platforms F1 and F2 to the sea target T; are the random errors of the observation distance, azimuth and elevation angle of the aerial platforms F1 and F2 to the sea target T; Define the observation values ​​of aerial platforms F1 and F2 on the sea cooperation platform C The observed true value Observation system error and observational random error The following relationship exists: in, They are the true values ​​of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the offshore cooperation platform C; They are the observation distance, azimuth and pitch angle system errors of the aerial platforms F1 and F2 to the offshore cooperation platform C; are the random errors of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the offshore cooperation platform C; Define the attitude measurements of the aerial platforms F1 and F2 and attitude truth Attitude system error and attitude random error The following relationship exists: in, are the true values ​​of the yaw angle, pitch angle, and roll angle of the aerial platforms F1 and F2 respectively; They are the yaw angle, pitch angle, and roll angle system errors of the aerial platforms F1 and F2 respectively; They are the random errors of yaw angle, pitch angle and roll angle of aerial platforms F1 and F2 respectively; By simultaneously observing the cooperative platform and the target at sea, the attitude angle is inversely solved using the high-precision position information provided by the cooperative platform in real time, thereby reducing the influence of the sensor observation system error and the attitude angle system error. Ideally, the observation information from the air platform to the sea cooperation platform Aerial platform attitude information and aerial platforms and offshore cooperation platform The position information of the offshore cooperation platform in the earth coordinate system can be obtained as follows:

3. The target state estimation method based on attitude correction-anti-error fusion according to claim 1 is characterized in that: The S2 specifically includes: Due to the observation information of the aerial platform to the maritime cooperation platform and aerial platform attitude information There is an error, the above equation does not hold, and the indicator function is constructed: Solving and correcting posture Make Track targets at sea using corrected attitude to improve target tracking accuracy; According to the above formula, the correction attitudes of the aerial platforms F1 and F2 are obtained respectively:

4. The target state estimation method based on attitude correction-anti-error fusion according to claim 1 is characterized in that: The S3 specifically includes: Based on the corrected posture, the position information of the target at the fusion center is obtained: Among them: M1, M2 are system error coefficients; is the systematic error term; W1 and W2 are random errors; Let N = [M1 M2][M1 - M2] T ([M1 - M2][M1 - M2] T ) -1 ; Construct the pseudo-measurement equation: W f =(E 3×3 -N)W1+(E 3×3 +N)W2 Among them, the error covariance matrix of W1 is The error covariance matrix of W2 is In summary, the formula can be written as: Z=2HX+W f Where: W f It is approximately zero-mean Gaussian white noise, and its error covariance matrix is:

5. A target state estimation system based on attitude correction-anti-error fusion based on the target state estimation method based on attitude correction-anti-error fusion as described in claims 1-4, characterized in that: The system specifically includes: A data acquisition module is used to acquire data, including observation information of the aerial platform on the offshore cooperation platform and targets, the aerial platform attitude information, and the location information of the aerial platform and the cooperation platform; A correction attitude calculation module is connected to the data acquisition module and is used to calculate the correction attitudes of the aerial platforms F1 and F2; The precise tracking module is connected to the correction posture calculation module, and integrates the correction posture with the anti-error algorithm model to achieve precise tracking of the target.

6. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the target state estimation method based on posture correction-anti-error fusion as described in any one of claims 1-4.

7. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the target state estimation method based on posture correction-anti-error fusion as described in any one of claims 1 to 4.

8. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the target state estimation system based on posture correction-anti-error fusion as described in claim 5.

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