Electronic countermeasure equipment aerial carrier motion trail simulation method based on residual error correction model

Abstract

The invention relates to an electronic countermeasure equipment aerial carrier motion trail simulation method based on a residual error correction model, and belongs to the technical field of airborne electronic countermeasure equipment testing. Inputting position information of an airborne electronic countermeasure equipment carrier in the geodetic coordinate system; inputting a position information sequence of the radar simulator in the process of performing relative motion with the airborne electronic countermeasure equipment carrier aircraft in the geodetic coordinate system; converting the position information of the radar simulator at n moments in the geodetic coordinate system into a coordinate sequence in a polar coordinate system taking the airborne electronic countermeasure equipment aerial carrier as an original point; accumulating the sequences to obtain a generated sequence; solving an estimation parameter for the differential equation by using a least square method; solving a predicted value of the relative position at the corresponding moment; constructing a residual sequence; constructing a residual correction model by using the residual sequence; and residual error fitting is carried out to improve the data precision. According to the method, the problem that the motion simulation track is inaccurate when the number of position data training samples is small in an existing method is solved.

Description

Technical Field

[0001] The invention relates to a method for simulating the motion trajectory of an electronic countermeasure equipment carrier based on a residual correction model, which is used for performance testing of airborne electronic countermeasure equipment and belongs to the technical field of airborne electronic countermeasure equipment testing. Background Art

[0002] When testing and evaluating key performance of airborne electronic countermeasure equipment such as direction finding and frequency measurement, it is often necessary to simulate the relative motion of the airborne electronic countermeasure equipment carrier relative to the radar signal simulator in order to restore the real electronic countermeasure scenario and obtain accurate test results.

[0003] The simulation of the relative motion of the carrier of airborne electronic countermeasure equipment with respect to the radar signal simulator is generally accomplished by the following method: simulating the motion trajectory of the carrier of airborne electronic countermeasure equipment, and controlling the amplitude and frequency of the electromagnetic signal radiated by the radar signal simulator according to the changes in the motion trajectory, thereby equivalently generating relative motion at the carrier under test.

[0004] There are currently two main methods for simulating the motion trajectory of an aircraft carrying airborne electronic countermeasure equipment. The first method is to calculate the motion trajectory from the perspective of motion dynamics by setting the initial coordinates and initial velocity or initial acceleration. Its disadvantage is that it can only achieve uniform or uniformly accelerated motion, which is quite different from the motion of the aircraft in the actual confrontation process, and the high requirements for target parameter estimation also limit the application of such methods. The second method is to restore the motion trajectory based on the position data collected during the actual motion of the aircraft, and predict the subsequent position. This method learns from the position data of the actual motion and performs extrapolated simulation. The resulting motion trajectory is more realistic than the first method, but in the simulation process, it is limited by the amount of position data training sample data, resulting in inaccurate generated trajectories. At the same time, generating too much trajectory simulation data can easily cause data jumps. Summary of the invention

[0005] The purpose of the present invention is to provide a method for simulating the motion trajectory of an electronic countermeasure equipment carrier based on a residual correction model, so as to solve the problem of inaccurate motion simulation trajectory when there are too few position data training samples in the existing method of simulating motion trajectory according to position data collected during the actual movement of the carrier, and the problem of uneven motion trajectory simulation motion curve caused by jump changes in data after too much trajectory simulation data is generated.

[0006] The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model of the present invention is special in that it comprises the following steps:

[0007] Step 1: Input the position information sequence of the airborne electronic countermeasure equipment carrier in the geodetic coordinate system. The position information sequence includes the longitude, latitude, and altitude of the airborne electronic countermeasure equipment carrier at n moments collected during the movement, which is recorded as the longitude sequence X (0) , Latitude sequence Y (0) , height sequence Z (0) ;

[0008] Step 2: Accumulate the position information sequence of the airborne electronic countermeasure equipment carrier at n moments to obtain the longitude sequence X (1) , Latitude sequence Y (1) , height sequence Z (1) ;

[0009] Step 3: Convert the longitude sequence X (1) , Latitude sequence Y (1) , height sequence Z (1) The n moments in time are considered as continuous variables, X (1) , Y (1) , Z (1) Considered as a function of time, a system of differential equations is established, denoted as the MGM (1, N) model;

[0010] Step 4: Use the least squares method to solve the MGM (1, Z) model and obtain the longitude sequence X (1) , Latitude sequence Y (1) , height sequence Z (1) The fitted value of

[0011] Step 5: Use the reduction formula described in step 4 Get the longitude sequence X (0) , Latitude sequence Y (0) , height sequence Z (0) The fitted value of The fitted value is used to simulate the values ​​at time n+1 and later;

[0012] Step 6: Use the value obtained in step 5 Get the predicted value and X (0) , Y (0) , Z (0) , construct the residual sequence

[0013] Step 7: Using the residual sequence Construct a residual correction model to perform residual fitting, correct the original data, and reduce the probability of sudden changes in the data;

[0014] Step 8: In the actual simulation process, residual fitting is performed multiple times based on the corrected data to improve the accuracy of the data.

[0015] Preferably, the longitude sequence X in step 1 (0) , latitude sequence Y (0) , height sequence Z (0) as follows:

[0016] X (0) =(X (0) (1),X (0) (2),X (0) (3),…X (0) (n)),

[0017] Y (0) =(Y (0) (1),Y (0) (2),Y (0) (3),…,Y (0) (n)),

[0018] Z (0) =(Z (0) (1),Z (0) (2),Z (0) (3),…,Z (0) (n)).

[0019] Preferably, the longitude sequence X in step 2 (1) , Latitude sequence Y (1) , height sequence Z (1) as follows:

[0020]

[0021]

[0022]

[0023] Preferably, the MGM (1, N) model described in step 3 is as follows, wherein X (1) Y (1) , Z (1) The rate of change of Y (1) X (1) , Z (1) The rate of change of Z (1) Y (1) , X (1) The change rate of is affected, and the unknown quantities a and b are the parameters to be solved;

[0024]

[0025] Preferably, the steps of solving the MGM (1, N) model by the least squares method described in step 4 are as follows:

[0026] The parameters of the MGM (1, N) model are:

[0027] where i=1,2,3

[0028] Let Y n =[(X (0) (1),…,X (0) (n)) T ,(Y (0) (1),…,Y (0) (n)) T ,(Z (0) (1),…,Z (0) (n)) Y ], discretize the above differential equations by difference method, and we can get the linear equation system Y n =BU, by the least square method we can get U = (B T B) - 1 B T Y n , that is, find the values ​​of A and B, that is, find the values ​​of unknown quantities a and b. At this time, the MGM (1, N) model described in step 3 can be determined, and X is obtained. (1) , Y (1) , Z (1) The fitted values ​​are as follows:

[0029]

[0030]

[0031]

[0032] Preferably, the reduction formula in step 5 is:

[0033]

[0034]

[0035]

[0036] Preferably, the residual sequence in step 6 is as follows:

[0037]

[0038]

[0039]

[0040] Preferably, the residual correction model in step 7 is:

[0041]

[0042]

[0043]

[0044] in,

[0045] Preferably, the model for performing residual fitting multiple times in step 8 is:

[0046]

[0047] Among them, m is the order of the residual correction model. The Y and Z models are the same as X, and the analogy can be deduced.

[0048] Compared with the prior art, the present invention has the following advantages:

[0049] The present invention provides a method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model. According to the position data collected during the actual motion of the carrier aircraft, the motion trajectory is restored, and the subsequent position is predicted, so that the obtained motion trajectory is more realistic; the method is expanded from the continuous GM (1,1) model grey differential equation, which can be used not only to simulate the value at the next moment, but also to simulate or predict the value at any moment; the method provides a residual correction model, which can effectively reduce the probability of a jump change in the data, and obtain a smoother and more realistic curve when predicting the long-term trajectory value of the carrier aircraft. In summary, the present invention can better simulate the motion trajectory of the airborne electronic countermeasure equipment carrier aircraft relative to the radar signal simulator, solve the problem of inaccurate motion simulation trajectory when the position data training samples are too few in the existing method of simulating motion trajectory according to the position data collected during the actual motion of the carrier aircraft, and solve the problem of motion trajectory simulation jump caused by jump changes in data due to excessive data generation, resulting in the simulation motion curve being not smooth. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a comparison chart of the X-coordinate fitting degree of the carrier motion trajectory;

[0051] Figure 2 This is a comparison chart of the y-coordinate fitting degree of the carrier motion trajectory;

[0052] Figure 3 This is a comparison chart of the z-coordinate fitting degree of the carrier motion trajectory;

[0053] Figure 4 This is a simulation diagram of the aircraft's motion trajectory. DETAILED DESCRIPTION

[0054] In order to better understand and implement, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It is also necessary to explain that, for ease of description, only parts related to the present invention are shown in the accompanying drawings, rather than all structures.

[0055] Example 1

[0056] Assume that the flight position coordinate of the carrier aircraft in the geodetic coordinate system is x (0) =

[0057] {x (0) (1),x (0) (2),…,x (0) (n)}、y (0) {y (0) (1),y (0) (2),…,y (0) (n)},

[0058] z (0) {z (0) (1),z (0) (2),…,z (0) (n)}, establish the MGM (1,3) model to generate the position coordinate data of the aircraft at the next moment. Obviously, this can obtain the position coordinate information at any moment in this stage. Then substitute the simulated value obtained by the MGM (1,3) model into the residual correction model, perform a residual correction modeling, and compare the correction value, the simulated value of the MGM (1,3) model and the actual value.

[0059] Assume that the first ten groups of historical position coordinates of the carrier are as shown in Table 1. The MGM (1,3) model is obtained through the first nine groups of coordinate data, and then the tenth group of coordinate data is simulated and compared with the actual tenth group of data, so as to verify the effectiveness and advancement of the simulation method proposed in this patent.

[0060] Table 1 Experimental data of 5 actual coordinates of the carrier position (10m)

[0061]

[0062] Take the first nine data. Accumulate and generate the data obtained in Table 1 to find the generated sequence:

[0063] X (1) (i) = {x (1) (i),y (1) (i),z (1) (i)}

[0064] And get B and Y n :

[0065]

[0066] Then the parameter estimation equation of the MGM (1,3) model is:

[0067] Y n =BU

[0068] By least squares estimation, we can get:

[0069]

[0070] Then the time parameters A and B of the MGM (1,3) model equation are:

[0071]

[0072] B=[823.7504 161.9047 3513.629]

[0073] The MGM (1,3) model can be established as:

[0074]

[0075] By solving the equations, we can get the approximate solution of the position coordinates with respect to time, as shown in Table 2:

[0076] Table 2-2MGM(1,3) model position coordinate simulation values ​​(10m)

[0077]

[0078] Substitute the data obtained from the MGM (1,3) model in the previous section into the formula above to calculate the third-order residual correction model. Compare the actual value, the MGM (1, N) simulation value and the residual correction value. The results are shown in Table 3:

[0079] Table 3: MGM (1,3) model and residual correction model fitting results (10m)

[0080] Table 3 (a) x coordinates

[0081]

[0082] Table 3 (b) y coordinates

[0083]

[0084] Table 3 (c) z coordinates

[0085]

[0086]

[0087] According to the relative error of the tenth set of data, we can get:

[0088]

[0089]

[0090] Among them, P 1 is the accuracy of the tenth set of coordinate data of MGM(1,3), P 2 is the accuracy of the tenth set of coordinate data after residual correction. It can be seen that after residual correction, the accuracy of the model has been significantly improved.

[0091] Based on the above data, the fitting effect diagram of each model aircraft motion is drawn, such as Figure 1 , Figure 2 , Figure 3 As shown. It can be seen that the simulation results of the MGM (1,3) model and the residual correction model are close to the actual values, and the simulation accuracy of the residual correction model is better than that of the MGM (1,3) model. From the relative error of simulating the next set of data, the effect of the residual correction model in simulating a set of data is also better than that of the MGM (1,3) model. Therefore, it can be considered that the MGM (1,3) model after residual correction is better in fitting with the actual value. Based on the residual correction value, the track diagram of the carrier aircraft is drawn, as shown in Figure 4 shown.

[0092] The above calculation examples of the present invention are only used to explain the calculation model and calculation process of the present invention in detail, and are not intended to limit the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model, characterized in that The following steps are involved: Step 1: Input the position information sequence of the airborne electronic countermeasure equipment carrier in the geodetic coordinate system. The position information sequence includes the longitude, latitude, and altitude of the airborne electronic countermeasure equipment carrier at n moments collected during the movement, which is recorded as the longitude sequence X (0) , Latitude sequence Y (0) , height sequence Z (0) ; Step 2: Accumulate the position information sequence of the airborne electronic countermeasure equipment carrier at n moments to obtain the longitude sequence X (1) , Latitude sequence Y (1) , height sequence Z (1) ; Step 3: Convert the longitude sequence X (1) , Latitude sequence Y (1) , height sequence Z (1) The n moments in time are considered as continuous variables, X (1) , Y (1) , Z (1) Considered as a function of time, a set of differential equations is established, denoted as the MGM (1, N) model; Step 4: Use the least squares method to solve the MGM (1, N) model and obtain the longitude sequence X (1) , Latitude sequence Y (1) , height sequence Z (1) The fitted value of Step 5: Use the reduction formula described in step 4 Get the longitude sequence X (0) , Latitude sequence Y (0) , height sequence Z (0) The fitted value of The fitted value is used to simulate the values ​​at time n+1 and later; Step 6: Use the value obtained in step 5 Get the predicted value and X (0) , Y (0) , Z (0) , construct the residual sequence Step 7: Using the residual sequence Construct a residual correction model to perform residual fitting, correct the original data, and reduce the probability of sudden changes in the data; Step 8: In the actual simulation process, residual fitting is performed multiple times based on the corrected data to improve the accuracy of the data.

2. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 1, characterized in that The longitude sequence X described in step 1 (0) , latitude sequence Y (0) , height sequence Z (0) as follows: X (0) =(X (0) (1),X (0) (2),X (0) (3),…X (0) (n)), AND (0) (And (0) (1),And (0) (2),And (0) (3),…,And (0) (n)), WITH (0) =(From (0) (1),From (0) (2),From (0) (3),…,From (0) (n))。 3. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 2, characterized in that The longitude sequence X described in step 2 (1) , Latitude sequence Y (1) , height sequence Z (1) as follows:

4. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 3 is characterized in that The MGM (1, N) model described in step 3 is as follows, where X (1) Y (1) , Z (1) The rate of change of Y (1) X (1) , Z (1) The rate of change of Z (1) Y (1) , X (1) The change rate of is affected, and the unknown quantities a and b are the parameters to be solved; 5. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 1, characterized in that The steps of solving the MGM (1, N) model using the least squares method described in step 4 are as follows: The parameters of the MGM (1, N) model are: where i = 1, 2, 3 Let Y n =[(X (0) (1), …, X (0) (n)) T , (Y (0) (1), …, Y (0) (n)) T , (Z (0) (1), …, Z (0) (n)) T ], discretize the above differential equations by difference method, and we can get the linear equation system Y n =BU, by the least square method we can get U = (B T B) -1 B T Y n , that is, find the values ​​of A and B, that is, find the values ​​of unknown quantities a and b. At this time, the MGM (1, N) model described in step 3 can be determined, and X is obtained. (1) , Y (1) , Z (1) The fitted values ​​are as follows:

6. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 1, characterized in that The reduction formula described in step 5 is:

7. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 1, characterized in that The residual sequence described in step 6 is as follows:

8. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 1, characterized in that The residual correction model described in step 7 is: in, 9. The method for simulating the motion trajectory of an electronic countermeasure equipment carrier aircraft based on a residual correction model according to claim 8, wherein the model for performing residual fitting multiple times in step 8 is: in, m is the order of the residual correction model. The Y and Z models are the same as X, and can be deduced by analogy.

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