A fast maneuvering detection method based on relative proportion integral amplification

Abstract

The present invention discloses a rapid maneuvering detection method based on relative proportion integral amplification, the method is as follows: construct different maneuvering characterization models through different motion characteristic factors to determine the motion mode; design a maneuvering probability solution function; design thresholds of motion characteristic factors of different motion modes, and calculate the matching degree parameters of the aircraft with each preset motion mode at this time by comprehensive filtering and estimating motion characteristic factors; solve the corresponding maneuvering probabilities of various motion modes, solve the relative proportions of different maneuvering probabilities, integrate the relative proportions of maneuvering probabilities to obtain a corrected integral maneuvering probability, and amplify the gap between the maneuvering probabilities corresponding to different motion modes; judge the motion mode of the aircraft by the corrected integral maneuvering probability. The present invention can distinguish a variety of prior motion modes of the aircraft by adopting a maneuvering characterization model, and realize rapid maneuvering detection of hypersonic aircraft by using the maneuvering probability solution and relative proportion integral amplification method.

Description

Technical Field

[0001] The invention relates to a rapid maneuvering detection method for a hypersonic aircraft, and in particular to a maneuvering probability solving method based on relative proportion integral amplification. Background Art

[0002] Hypersonic aircraft are fast, highly maneuverable, and their trajectories are difficult to predict, making them difficult to intercept. To conduct efficient interception, it is necessary to quickly and accurately detect and estimate the target's motion state in order to accurately predict its trajectory. However, the unknown maneuvering characteristics of the aircraft require the study of its maneuvering characteristics and corresponding maneuvering detection technology in order to quickly determine the target's maneuvering state and provide real-time information to meet interception requirements. Summary of the invention

[0003] The purpose of the present invention is to provide a rapid maneuvering detection method based on relative proportion integral amplification. The method can distinguish multiple prior motion modes of an aircraft by adopting a maneuvering characterization model, and utilizes the method of maneuvering probability solution and relative proportion integral amplification to achieve rapid maneuvering detection of a hypersonic aircraft.

[0004] The objective of the present invention is achieved through the following technical solutions:

[0005] A rapid maneuvering detection method based on relative proportion integral amplification comprises the following steps:

[0006] Step 1: Analyze the motion characteristic factors of the hypersonic vehicle when it maneuvers, build different maneuver characterization models through different motion characteristic factors, and determine the motion mode;

[0007] Step 2: Design the probability threshold based on the maneuver characterization model and design the maneuver probability solution function;

[0008] Step 3: In order to reduce the misjudgment of maneuver mutation detection due to data noise and fluctuation, the actual motion characteristic factor of the current system is filtered by the TD tracking differentiator, the thresholds of the motion characteristic factors of different motion modes are designed, and the motion characteristic factors estimated by the comprehensive filtering are used to calculate the matching degree parameters of the aircraft at this time with each preset motion mode;

[0009] Step 4: Substitute the prior probability threshold and the solved matching degree parameter into the maneuver probability solving function to solve the corresponding maneuver probability of each motion mode. In order to speed up the maneuver detection speed, solve the relative proportion of different maneuver probabilities, integrate the relative proportion of maneuver probabilities to obtain the corrected integral maneuver probability, and magnify the gap between the maneuver probabilities corresponding to different motion modes;

[0010] Step 5: Determine the motion mode of the aircraft by the modified integral maneuver probability, and determine whether the motion mode switching conditions are met. If the motion mode switching conditions are met, the motion mode switching is performed; if the motion mode switching conditions are not met, the motion mode switching is not performed, and the rapid maneuver detection of the hypersonic aircraft is completed.

[0011] Compared with the prior art, the present invention has the following advantages:

[0012] (1) By introducing the maneuver characterization model, motion characteristic factors, maneuver probability solution function and matching degree parameters, mathematical modeling and quantitative analysis of the maneuver detection of hypersonic aircraft are carried out.

[0013] (2) A tracking differentiator is used to pre-process the aircraft motion characteristic factors to reduce the misjudgment of maneuver detection caused by data noise.

[0014] (3) Design a relative proportion of maneuver probability integral amplification link to amplify the gap between maneuver probabilities of different motion modes and speed up maneuver detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of a fast maneuvering detection method based on relative proportion integral amplification;

[0016] Figure 2 Acceleration results are estimated for the lateral trajectory;

[0017] Figure 3 The results of maneuver detection with different cumulative judgment times. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is further described below in conjunction with the accompanying drawings, but is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention should be included in the protection scope of the present invention.

[0019] The present invention provides a rapid maneuvering detection method based on relative proportion integral amplification, such as Figure 1 As shown, the method comprises the following steps:

[0020] Step 1: When a hypersonic vehicle performs maneuvers, analyze its motion characteristic factors, build different maneuver characterization models through different motion characteristic factors, and determine the motion mode. The specific steps are as follows:

[0021] When a hypersonic vehicle is maneuvering, analyze the changes in its different motion characteristic factors. Assuming that there are 7 preset motion modes, you can choose These eight quantities are used as motion characteristic factors to characterize seven motion modes, among which a xis the component of acceleration in the x-axis direction, a y is the component of acceleration in the y-axis direction, a z is the component of acceleration in the z-axis direction, is the component of the rate of change of acceleration in the x-axis direction, is the component of the rate of change of acceleration in the y-axis direction, is the component of the rate of change of acceleration in the z-axis direction, θ a is the direction of acceleration, is the direction of the acceleration change rate. So we can get the maneuver characterization model M, where Seven possible motion modes of the aircraft are characterized.

[0022] Step 2: Define the probability threshold based on the maneuver characterization model and design the following maneuver probability solution function:

[0023]

[0024] Where K ji is the prior probability threshold of each motion characteristic factor in the 7 motion modes, i=1…7 represents the 7 motion modes, j=18 represents These 8 different motion characteristic factors. It is known that the matching degree parameter p of each motion mode of the aircraft at this time i (t) and the corresponding prior probability threshold K ji , the maneuver probability f of the aircraft for 7 motion modes is solved by the maneuver probability solving function i (t).

[0025] Step 3: In order to reduce the misjudgment of maneuver mutation detection caused by data noise and fluctuation, the TD tracking differentiator is used to filter the actual motion characteristic factor v(t) of the current system, and two output signals v1 and v2 are generated according to the given reference input v(t), where v1 tracks v(t) according to the designed reasonable transition process, and v2 tracks The thresholds of motion characteristic factors of different motion modes are designed, and the motion characteristic factors estimated by comprehensive filtering are used to calculate the matching degree parameters of the current system of the aircraft with each preset motion mode. The specific steps are as follows:

[0026] Step 3.1: Set corresponding thresholds for each model motion characteristic factor:

[0027]

[0028] Step 3.2: Use a discrete fastest tracking differentiator to filter the actual motion characteristic factor v(t) of the current system, and generate two output signals v1 and v2 according to the given reference input v(t). The tracking differentiator is designed as:

[0029]

[0030] Where, k represents the kth step data; e is the tracking error; h is the sampling step; r0 and h0 are adjustable parameters, r0 determines the tracking speed, and h0 determines the filtering effect of the tracking differentiator on the noise signal. Its expansion plays a good filtering role and is called the filtering factor of the tracking differentiator. The algorithm design of the function fhan(e,v2,r0,h0) is:

[0031]

[0032] Where a, a0, d, d0, y are all intermediate variables for solving the function; sgn(·) is the symbolic function.

[0033] Step 3.3: Obtain the maneuver characterization vector M(t) of the aircraft at this time:

[0034] The filtered estimated values ​​of the motion characteristic factors of all motion modes are compared with the corresponding items in the prior threshold and judged. If the motion characteristic factor is less than the threshold, the result is false (i.e. 0); if the motion characteristic factor is greater than or equal to the threshold, the result is true (i.e. 1), and the maneuver characterization vector M(t) of the aircraft at this time can be solved.

[0035] Step 3.4: Calculate the matching degree parameter p i (t):

[0036] Match the maneuver characterization vector M(t) with [M1, M2, M3, M4, M5, M6, M7] in the maneuver characterization model M in order. If the matches are the same, the result is true (i.e. 1); if the matches are different, the result is false (i.e. 0). The matching degree p between the aircraft and each preset motion mode can be solved. i (t):

[0037]

[0038] Among them, i=1…7 represents 7 kinds of sports modes, p i (a x ),p i (a y ),p i (a z ), p i (θ a ), They respectively represent the matching degree of 8 different motion characteristic factors in the i-th motion mode.

[0039] For example, when M(t)=[10110100], the result of matching with the sixth row M6 of the matrix M (ie, the sixth possible motion mode) is p1(t)=[11011011].

[0040] Step 4: Substitute the prior probability threshold and the solved matching degree parameter into the maneuver probability solving function to solve the maneuver probability f of each motion mode i (t), in order to speed up the maneuver detection, the relative proportion of different maneuver probabilities is solved i ratio (t), the relative proportion of the maneuver probability is integrated to obtain the corrected integrated maneuver probability F i (t), amplify the difference between the maneuver probabilities corresponding to different motion modes. The specific steps are as follows:

[0041] Step 4.1: Set the prior probability threshold K ji The matching degree parameter p1(t) calculated by the solution is brought into the maneuver probability solution function to calculate the maneuver probability f of various motion modes i (t).

[0042] Step 4.2: Calculate the relative proportion of the maneuver probability of each movement mode in all movement modes:

[0043]

[0044] Step 4.3: The relative proportion f of the maneuver probability of each type of motion mode i ratio (t) Integrate to obtain the corrected integral maneuver probability F i (t) = ∫f i ratio (t)dt. The relative proportion integral amplification link can amplify the gap between various motion modes and speed up the detection speed.

[0045] Step 5: Determine the motion mode of the aircraft by the modified integral maneuver probability, and determine whether the motion mode switching condition is met. If the motion mode switching condition is met, the motion mode switching is performed; if the motion mode switching condition is not met, the motion mode switching is not performed, and the rapid maneuver detection of the hypersonic aircraft is completed. The specific steps are as follows:

[0046] Step 5.1: Given the initial value of maneuver probability, set the relevant thresholds and motion mode switching conditions.

[0047] Step 5.2: After each filtering step, the model characteristic parameters are judged, and the maneuver probability F is calculated by solving the maneuver probability model function i (t).

[0048] Step 5.3: Determine whether a preset motion mode switching condition is met. If the motion mode switching condition is met, the motion mode switching is performed; if the motion mode switching condition is not met, the motion mode switching is not performed.

[0049] Step 5.4: Repeat the process from step 5.1 to step 5.3 until the rapid maneuvering test of the hypersonic aircraft is completed.

[0050] A rapid maneuver test was conducted on the reentry phase of a hypersonic vehicle. The maneuver test results are as follows: Figure 2-3 As shown. Figure 2 The lateral acceleration estimation results of the reentry trajectory shown in Figure 2 show that the vehicle performed lateral maneuvers at 420s, 620s, and 1040s. Figure 3 It can be seen from the maneuver detection results with different cumulative judgment times that at the three time points when the aircraft exhibits lateral maneuvers, the maneuver detection flag bit jumps from 0 to 1, that is, the maneuver detection method provided by the present invention is fast and effective.

Claims

1. A rapid maneuvering detection method based on relative proportion integral amplification, characterized in that The method comprises the following steps: Step 1: When a hypersonic vehicle maneuvers, analyze its motion characteristic factors, build different maneuver characterization models through different motion characteristic factors, and determine the motion mode. The specific steps are as follows: When a hypersonic vehicle is maneuvering, the changes in different motion characteristic factors are analyzed. Assuming that 7 motion modes are preset, select As the motion characteristic factor, 7 motion modes are characterized, among which a x is the component of acceleration in the x-axis direction, a y is the component of acceleration in the y-axis direction, a z is the component of acceleration in the z-axis direction, is the component of the rate of change of acceleration in the x-axis direction, is the component of the rate of change of acceleration in the y-axis direction, is the component of the rate of change of acceleration in the z-axis direction, θ a is the direction of acceleration, is the direction of the acceleration change rate; the maneuver characterization model M is obtained, where Characterizes seven possible motion modes of the aircraft; Step 2: Based on the maneuver characterization model, a probability threshold is designed, and a maneuver probability solution function is designed. The maneuver probability solution function is: Where K ji is the prior probability threshold of each motion characteristic factor in the 7 motion modes, i = 1...7 represents the 7 motion modes, j = 1...8 represents It is known that the matching degree parameter p of each motion mode of the aircraft at this time i (t) and the corresponding prior probability threshold K ji , the maneuver probability f of the aircraft for 7 motion modes is solved by the maneuver probability solving function i (t); Step 3: In order to reduce the misjudgment of maneuver mutation detection due to data noise and fluctuation, the actual motion characteristic factor of the current system is filtered by the TD tracking differentiator, the thresholds of the motion characteristic factors of different motion modes are designed, and the motion characteristic factors estimated by the comprehensive filtering are used to calculate the matching degree parameters of the aircraft at this time with each preset motion mode; Step 4: Substitute the prior probability threshold and the solved matching degree parameter into the maneuver probability solving function to solve the corresponding maneuver probability of each motion mode. In order to speed up the maneuver detection speed, solve the relative proportion of different maneuver probabilities, integrate the relative proportion of maneuver probabilities to obtain the corrected integral maneuver probability, and magnify the gap between the maneuver probabilities corresponding to different motion modes; Step 5: Determine the motion mode of the aircraft by the modified integral maneuver probability, and determine whether the motion mode switching conditions are met. If the motion mode switching conditions are met, the motion mode switching is performed; if the motion mode switching conditions are not met, the motion mode switching is not performed, and the rapid maneuver detection of the hypersonic aircraft is completed.

2. The rapid maneuvering detection method based on relative proportion integral amplification according to claim 1 is characterized in that The specific steps of step 3 are as follows: Step 3.1: Set corresponding thresholds for each model motion characteristic factor: Step 3.2: Use a discrete fastest tracking differentiator to filter the actual motion characteristic factor v(t) of the current system, and generate two output signals v1 and v2 according to the given reference input v(t), where v1 tracks v(t) according to the designed reasonable transition process, and v2 tracks Step 3.3: Obtain the maneuver characterization vector M(t) of the aircraft at this time: Compare the filtered estimated values ​​of the motion characteristic factors of all motion modes with the corresponding items in the prior threshold and judge. If the motion characteristic factor is less than the threshold, the result is false, that is, 0; if the motion characteristic factor is greater than or equal to the threshold, the result is true, that is, 1, and the maneuver characterization vector M(t) of the aircraft at this time is solved; Step 3.4: Calculate the matching degree parameter p i (t): Match the maneuver characterization vector M(t) with [M1,M2,M3,M4,M5,M6,M7] in the maneuver characterization model M in order. If the matches are the same, the result is true; if the matches are different, the result is false. The matching degree p between the aircraft and each preset motion mode can be solved. i (t): Among them, i=1...7 represents 7 kinds of sports modes. They respectively represent the matching degree of 8 different motion characteristic factors in the i-th motion mode.

3. The rapid maneuvering detection method based on relative proportion integral amplification according to claim 2 is characterized in that The tracking differentiator is designed as: In the formula, k represents the kth step data; e is the tracking error; h is the sampling step; r0 and h0 are adjustable parameters, r0 determines the tracking speed, and h0 determines the filtering effect of the tracking differentiator on the noise signal; the algorithm design of the function fhan(e,v2,r0,h0) is: Where a, a0, d, d0, y are all intermediate variables for solving the function; sgn(·) is the symbolic function.

4. The rapid maneuvering detection method based on relative proportion integral amplification according to claim 2 is characterized in that The specific steps of step 4 are as follows: Step 4.1: Set the prior probability threshold K ji The matching degree parameter p1(t) calculated by the solution is brought into the maneuver probability solution function to calculate the maneuver probability f of various motion modes i (t); Step 4.2: Calculate the relative proportion of the maneuver probability of each movement mode in all movement modes: Step 4.3: Relative proportion of maneuver probability of each movement mode Integrate to get the corrected integral maneuver probability 5. The rapid maneuvering detection method based on relative proportion integral amplification according to claim 4 is characterized in that The specific steps of step 5 are as follows: Step 5.1: Given the initial value of maneuver probability, set the relevant thresholds and motion mode switching conditions; Step 5.2: After each filtering step, the model characteristic parameters are judged, and the maneuver probability F is calculated by solving the maneuver probability model function. i (t); Step 5.3: Determine whether a preset motion mode switching condition is met. If the motion mode switching condition is met, the motion mode is switched. If the motion mode switching condition is not met, the motion mode is not switched. Step 5.4: Repeat the process from step 5.1 to step 5.3 until the rapid maneuvering test of the hypersonic aircraft is completed.

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