A target state estimation method based on attitude correction and robust fusion

Abstract

This invention belongs to the field of target state estimation technology and discloses a target state estimation method based on attitude correction-robust fusion. The method comprises acquiring data, including observation information of an aerial platform of a cooperating offshore platform and a target, the attitude information of the aerial platform, and the position information of the aerial platform and the cooperating offshore platform; calculating the corrected attitudes of the aerial platforms F1 and F2; and fusing the corrected attitudes with a robust algorithm model to achieve precise target tracking. The invention integrates attitude correction and robust algorithms to simultaneously mitigate sensor observation system errors and attitude angle system errors. Finally, it introduces an interacting multi-model to achieve state estimation of maneuvering targets 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 fields 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, communications, control, robotics, and space exploration. State estimation theory aims to accurately estimate target state variables such as position, velocity, and acceleration from a series of observations. Kalman filtering is a classic state estimation method for linear state-space models with Gaussian noise. For nonlinear state-space models with heavy-tailed non-Gaussian noise and heavy-tailed skewed non-Gaussian noise, high-precision state estimation methods such as high-order difference cubature Kalman filters, Gaussian approximation filters based on quadrature point propagation, and particle filters have been proposed. Furthermore, methods based on random set frameworks, such as probability hypothesis density filtering and multi-Bernoulli filtering, play an important role in multi-target state estimation.

[0003] During the target state estimation process, the sensor observation system error and the platform attitude system error will have a significant impact on the state estimation accuracy and track association of the entire process. Therefore, 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 auxiliary beacons with different fields of view [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 attitude angle error has a significant impact on the UAV target state estimation. However, it only considers the influence of 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 presence of system errors in the coordinated air defense early warning system of airborne radar and ground-based radar. However, it only considers the influence of sensor observation system errors. Summary of the Invention

[0005] In response to 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 achieved by a target state estimation method based on attitude correction-anti-error fusion, the method comprising:

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

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

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

[0010] Furthermore, the S1 specifically includes:

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

[0012]

[0013] in, are the true values ​​of the observation distance, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2 respectively; are the observation range, azimuth and elevation system errors of the aerial platforms F1 and F2 to the sea target T respectively; 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 and the observed true value Observation system error and observational random error The following relationship exists:

[0015]

[0016] in, are the true values ​​of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the maritime cooperation platform C; are the observation range, azimuth and pitch angle system errors of the aerial platforms F1 and F2 to the maritime 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 the true value of posture Attitude system error and attitude random error The following relationship exists:

[0018]

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

[0020] By simultaneously observing the cooperative platform and the maritime target, the high-precision position information provided by the cooperative platform in real time is used to reversely resolve the attitude angle and reduce the influence of the sensor observation system error and the attitude angle system error.

[0021] Ideally, based on the observation information of the aerial platform on the maritime 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] Furthermore, 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 the 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] Furthermore, 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-robust fusion based on the target state estimation method based on attitude correction-robust fusion, the system specifically comprising:

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

[0043] The correction attitude calculation module is connected to the data acquisition module and is used to calculate the correction attitude 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 posture 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 posture 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 posture 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 mitigate sensor observation system errors and attitude angle system errors;

[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 This 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 This is a structural diagram of a target state estimation system based on attitude correction and robust fusion provided by an embodiment of the present invention;

[0053] Figure 3 This 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 solutions 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 intended 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: Acquire data, including observation information of the aerial platform on the maritime cooperative platform and targets, aerial platform attitude information, and location information of the aerial platform and cooperative platform;

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

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

[0060] Said S1 specifically includes:

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

[0062]

[0063] in, are the true values ​​of the observation distance, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2 respectively; are the observation range, azimuth and elevation system errors of the aerial platforms F1 and F2 to the sea target T respectively; 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 and the observed true value Observation system error and observational random error The following relationship exists:

[0065]

[0066] in, are the true values ​​of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the maritime cooperation platform C; are the observation range, azimuth and pitch angle system errors of the aerial platforms F1 and F2 to the maritime 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 the true value of posture Attitude system error and attitude random error The following relationship exists:

[0068]

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

[0070] By simultaneously observing the cooperative platform and the maritime target, the high-precision position information provided by the cooperative platform in real time is used to reversely resolve the attitude angle and reduce the influence of the sensor observation system error and the attitude angle system error.

[0071] Ideally, based on the observation information of the aerial platform on the maritime 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 the 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-robust fusion based on the target state estimation method based on attitude correction-robust 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 maritime cooperative platform and targets, aerial platform attitude information, and location information of the aerial platform and cooperative platform;

[0093] The correction attitude calculation module is connected to the data acquisition module and is used to calculate the correction attitude 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 posture 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 posture correction and robust 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 with a total simulation time of 200 s. The locations of observation platforms 1 and 2 were set at [507.53.5] km and [1283.5] km, respectively. The initial position of the cooperation platform was at the fusion center, moving 2000 m in the direction of a 90° azimuth angle. The initial position of the target was at a distance of 200 km from the fusion center at a 0° azimuth angle.

[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 target state estimation trajectory diagram, such as Figure 3 As shown in the simulation diagram, the present invention can achieve better state estimation of the target, and the target state estimation error of the terminal 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 portion can be implemented using dedicated logic; the software portion can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the above-mentioned devices and methods can be implemented using computer-executable instructions and / or contained in processor control code, for example, 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. The devices and 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, 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, or can be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

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

Claims

1. A target state estimation method based on attitude correction-robust fusion, characterized in that: The method includes: S1: Acquire the observation information of the aerial platform on the maritime cooperation platform and maritime targets, the aerial platform attitude information, and the position information of the aerial platform and the maritime cooperation platform; S2: Calculate the corrected attitudes of the aerial platforms F1 and F2; S3: Integrate the corrected posture with the robust algorithm model to achieve accurate tracking of the target; Said S1 specifically includes: Define the observation values ​​of the aerial platforms F1 and F2 on the sea target T and the observed true value Observation system error and observational random error The following relationship exists: in, are the true values ​​of the observation distance, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2 respectively; are the observation range, azimuth and elevation system errors of the aerial platforms F1 and F2 to the sea target T respectively; are the random errors of the observation range, azimuth and elevation angle of the sea target T by the aerial platforms F1 and F2 respectively; Define the observation values ​​of aerial platforms F1 and F2 on the sea cooperation platform C and the observed true value Observation system error and observational random error The following relationship exists: in, are the true values ​​of the observation distance, azimuth and pitch angle of the aerial platforms F1 and F2 to the maritime cooperation platform C; are the observation range, azimuth and pitch angle system errors of the aerial platforms F1 and F2 to the maritime 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 the true value of posture Attitude system error and attitude random error The following relationship exists: in, are the true values ​​of the yaw, pitch, and roll angles of the aerial platforms F1 and F2 respectively; are the yaw angle, pitch angle, and roll angle system errors of the aerial platforms F1 and F2 respectively; are the random errors of yaw, pitch and roll angles of the aerial platforms F1 and F2 respectively; Ideally, based on the observations of the aerial platform to the maritime partner platform Aerial platform attitude measurement values and aerial platform location information and offshore cooperation platform location information Xg C The position of the offshore cooperation platform in the earth coordinate system is obtained as: The S2 specifically includes: Construct indicator function: Solving and correcting the posture Make Tracking of maritime targets using corrected attitude; According to the above formula, the correction attitudes of the aerial platforms F1 and F2 are obtained respectively The S3 specifically includes: Based on the corrected attitude, the position information of the maritime 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 Simplified from the formula in S3 above, we get: Z=2HX+W f Where: W f It is approximately zero-mean Gaussian white noise, and its error covariance matrix is:

2. A target state estimation system based on attitude correction-robust fusion based on the target state estimation method based on attitude correction-robust fusion according to claim 1, 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 maritime cooperative platform and targets, aerial platform attitude information, and location information of the aerial platform and cooperative platform; The correction attitude calculation module is connected to the data acquisition module and is used to calculate the correction attitude 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.

3. 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 performs the steps of the target state estimation method based on posture correction-anti-error fusion as claimed in claim 1.

4. 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 claimed in claim 1.

5. 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 2.

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