CN114662285A - Intelligent resolving method for fire control model of high-speed aircraft - Google Patents

Intelligent resolving method for fire control model of high-speed aircraft Download PDF

Info

Publication number
CN114662285A
CN114662285A CN202210196520.9A CN202210196520A CN114662285A CN 114662285 A CN114662285 A CN 114662285A CN 202210196520 A CN202210196520 A CN 202210196520A CN 114662285 A CN114662285 A CN 114662285A
Authority
CN
China
Prior art keywords
target
model
speed
missile
aircraft
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210196520.9A
Other languages
Chinese (zh)
Inventor
刘燕斌
杨犇
陈金宝
陈柏屹
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing University of Aeronautics and Astronautics
Original Assignee
Nanjing University of Aeronautics and Astronautics
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing University of Aeronautics and Astronautics filed Critical Nanjing University of Aeronautics and Astronautics
Priority to CN202210196520.9A priority Critical patent/CN114662285A/en
Publication of CN114662285A publication Critical patent/CN114662285A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G06F17/13—Differential equations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/15—Vehicle, aircraft or watercraft design

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Mathematical Analysis (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Computational Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Geometry (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Computer Hardware Design (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • Operations Research (AREA)
  • Automation & Control Theory (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Aiming, Guidance, Guns With A Light Source, Armor, Camouflage, And Targets (AREA)

Abstract

The invention discloses an intelligent resolving method of a fire control model of a high-speed aircraft, which comprises the following steps: step 1, establishing an agent model of a high-speed aircraft airborne launching platform considering flight-push coupling according to existing data; step 2, constructing a fire control model of the high-speed aircraft platform, wherein the fire control model comprises a target motion prediction model, a missile outer trajectory model and a fire control hit problem resolving model; and 3, solving an attack area by combining an Archimedes optimization algorithm according to the flight characteristics of the high-speed aircraft, and reversely solving an initial instruction signal of the aircraft. The method has few control parameters and better robustness, and can solve the optimization problem by generating the objective function value with the minimum error.

Description

Intelligent resolving method for fire control model of high-speed aircraft
Technical Field
The invention belongs to the technical field of high-speed aircraft control, and relates to an intelligent calculation method for a fire control model of a high-speed aircraft.
Background
In recent years, research on high-speed aircrafts and fire control methods has been intensified in various countries. Moreover, unlike conventional aircraft, reusable high speed aircraft perform tasks at a lower cost. Moreover, the flying mode of the aircraft is more flexible due to the extremely fast flying speed and the ultra-strong maneuverability. The aviation fire control system is an important component of the high-speed flight carrier; the development of the existing artificial intelligence technology brings a new direction to a future fire control system, and the intellectualization of the aviation fire control system is realized on the basis of improving the informatization level, so that the development direction of the aviation fire control system is held, the development of the aviation fire control system is an important task, and the intelligent fire control system has a very wide application scene. However, compared with the conventional aircraft, the flight speed of the high-speed aircraft is remarkably increased, the flight environment of the high-speed aircraft is more complex, the disturbed frequency is high, and therefore the high-speed aircraft has the characteristics of short system response time and high real-time performance, more new requirements are provided for a fire control system, the calculation accuracy requirement for algorithm calculation is also improved, and a new intelligent algorithm needs to be explored to optimize the conventional fire control calculation method. Most of the application objects of the existing firepower control method are subsonic/supersonic manned aircrafts; however, the research on the fire control method of the high-speed aircraft is lacked. Therefore, in order to meet the fire control needs of future high-speed aircrafts, it is necessary to design an intelligent fire control calculation strategy suitable for the high-speed aircrafts.
Disclosure of Invention
The invention aims to solve the technical problem of providing an intelligent calculation method of a fire control model of a high-speed aircraft, which can solve the optimization problem by generating an objective function value with the minimum error.
In order to solve the technical problem, the invention provides an intelligent calculation method of a fire control model of a high-speed aircraft, which comprises the following steps:
step 1, establishing an agent model of a high-speed aircraft airborne launching platform considering flight-push coupling according to existing data;
step 2, constructing a fire control model of the high-speed aircraft platform, wherein the fire control model comprises a target motion prediction model, a missile outer trajectory model and a fire control hit problem resolving model;
and 3, solving an attack area by combining an Archimedes optimization algorithm according to the flight characteristics of the high-speed aircraft, and reversely solving an initial instruction signal of the aircraft.
Preferably, in step 1, establishing an agent model of a high-speed aircraft airborne launching platform considering flight-push coupling according to existing data specifically includes the following steps:
step 11, assuming that the aircraft flies in the rotating spherical ground, deducing to obtain a nonlinear mathematical model of the high-speed aircraft in the rotating spherical ground;
and step 12, sampling data according to the aerodynamic data, the geometric parameters and the propulsion coefficient of the aircraft in the existing database, fitting a polynomial to the sampled hypersonic velocity section data, and performing model evaluation on the fitted polynomial proxy model by using a goodness-of-fit test method after fitting.
Preferably, in step 2, establishing the target motion prediction model specifically includes: predicting the target by adopting an interactive multi-model algorithm, and decomposing the motion mode of the target into the synthesis of the following motion state models:
(1) a CV model;
when the target does not move, namely does uniform linear motion or uniform acceleration linear motion, the following second-order constant-speed CV models are respectively adopted;
assuming that the target does uniform linear motion, the target displacement is recorded as x (t), and the speed is recorded as x (t)
Figure BDA0003526033900000025
Under the condition that random disturbance exists in the target speed, the speed random disturbance is assumed to have a mean value of zero and a variance of delta2White gaussian noise a (t);
taking system state variables
Figure BDA0003526033900000021
According to Newton's law of motion, there are
Figure BDA0003526033900000022
Written in matrix form as
Figure BDA0003526033900000023
I.e. CV model of
Figure BDA0003526033900000024
Wherein, A (t) is the system matrix of the model, and B (t) is the input matrix.
(2) A CT model;
when the target makes constant turning motion with constant speed and constant direction but changing moment, the CT model is used for describing, and the discrete time domain form of the CT model is expressed as follows:
Figure BDA0003526033900000031
in the formula, xkAnd ykThe position components of the target state in the cartesian coordinate system along the x-axis and y-axis directions at time k,
Figure BDA0003526033900000032
and
Figure BDA0003526033900000033
for the corresponding velocity component at time k,
Figure BDA0003526033900000034
and
Figure BDA0003526033900000035
for corresponding mean values of zero variance q2White noise in the Gaussian process, w is a constant turning rate and can reflect the maneuvering condition of a target, p is a radar sampling interval, and a state transition equation describes the time from the moment k to the moment k +1A recurrence relation of the target state;
(3) a Xinge model;
the Singer model is a first-order time correlation model with the acceleration mean value of zero, and assuming that the target maneuvering acceleration time correlation function is in an exponential decay form, the time correlation function Ra (τ) of the Singer model is as follows:
Figure BDA0003526033900000036
in the formula:
Figure BDA0003526033900000037
a is the undetermined parameter that determines the target maneuver characteristics within the interval (t, t + τ). a (t) is the acceleration of the maneuver,
Figure BDA0003526033900000038
is the maneuvering acceleration variance.
Preferably, in step 2, the establishment of the missile outer trajectory model specifically comprises: when the high-speed aircraft is used as a carrier throwing platform, the building process of the model is different from that of the traditional aircraft, and the initial throwing speed and the initial throwing height are changed due to the flight characteristics of the aircraft; the launching height is closer to the adjacent space than the traditional aircraft, and the initial launching speed is also faster. Therefore, in the process of establishing the model, the problems of centrifugal acceleration caused by the curvature of the earth and coriolis acceleration caused by rotation need to be considered.
Preferably, in the step 2, in the air-to-air task of the high-speed aircraft, the aircraft carrying platform is a reusable flight-push coupled high-speed aircraft, so that the maneuvering performance is excellent, the flight envelope is large, and the comprehensive performance of the platform is greatly improved compared with that of the traditional aircraft. The high performance of the platform can reduce the requirement of the throwing object carried by the platform compared with the traditional aircraft; for example, in the releasing process, the released object is large in initial speed, so that the released object can be free of power, and an unpowered guidance mode can be considered, so that the releasing cost is reduced. The establishment of the fire control hit problem solving model specifically comprises the following steps: the method adopts a rapid simulation method for simulation in fire control emission, and specifically comprises the following steps:
(1) the missile adopts a proportional guidance law, and the action of a control system is not considered;
(2) solving a motion differential equation set of the missile by using a rapid variable step length integration method;
(3) the program is optimally designed, and the operation speed is improved by means of structure modularization and the like;
establishing a mathematical model of the aerial fire control task executed by the high-speed aircraft carrier throwing platform and the visual angular velocity of the missile and the target
Figure BDA0003526033900000041
Is composed of
Figure BDA0003526033900000042
Rate of change of distance
Figure BDA0003526033900000043
Is composed of
Figure BDA0003526033900000044
Wherein, V1Speed of the carrier, VM-target speed, r-target distance, theta-carrier speed declination, q-line-of-sight angle, thetaM-target velocity inclination angle, ηM-target heading angle, η -vehicle heading angle, q0Is the initial value of the line-of-sight angle between the missile and the target, r0The distance between the missile and the target is an initial value, and delta t is the target flight time;
the equation for the motion characteristic of the target is described by the following equation:
Figure BDA0003526033900000045
wherein T is the time of flight, θ, of the target timed at the missile launch instantM0Initial value of target velocity inclination angle, ηM0Initial value of target course angle, GMIs the subject of a mobile overload,
Figure BDA0003526033900000046
target rate of change of speed inclination, when GMWhen the value is 0, the target moves linearly at a constant speed, and when G is equal toMWhen not equal to 0, the target does constant-speed circular motion;
integrating the above equation to obtain:
θM＝θM(θM0,GM,VM,T) (9)
θM0＝q0-ηM0
wherein, thetaM0Initial value of target velocity inclination angle, ηM0-a target course angle initial value;
after the acceleration of the missile is integrated, the velocity value of the missile at any moment is obtained
Figure BDA0003526033900000047
In the formula, V0Is the initial velocity of the missile,
Figure BDA0003526033900000048
the missile speed change rate is shown.
The proportional guidance equation of the missile is
Figure BDA0003526033900000051
In the formula, K is a proportional guidance coefficient,
Figure BDA0003526033900000052
-rate of change of speed declination;
the motion of the target not only affects the motion characteristics of the target, but also affects the guidance law of the missile:
Figure BDA0003526033900000053
in the formula (I), the compound is shown in the specification,
Figure BDA0003526033900000054
is the rate of change of the line of sight angle.
The fire control model of the high-speed aircraft airborne delivery platform is as follows:
Figure BDA0003526033900000055
based on a rapid simulation calculation equation set in the established fire control model, under the determined initial condition, starting to calculate the parameter change of each point of the missile in the attack process by using the maximum power range of the missile as an initial value of the distance, judging whether the missile hits a target or not according to hit limiting conditions specified by missile characteristics such as hit miss amount and the like, if the missile does not hit the target, subtracting the miss amount from the distance as the initial value of the next calculation, and circularly calculating in such a way to finally obtain the maximum launching distance of the missile; in the same way, the minimum launching distance of the missile can be obtained, and the initial value q is continuously changed0Calculating to finally obtain a missile attack area;
the integration is performed in a program with variable step size: when the calculation is started, a larger step length is selected, and when the missile approaches or hits a target, a smaller step length is selected, so that the calculation speed is greatly increased under the condition of meeting a certain precision.
Preferably, in step 3, different initial missile launching line-of-sight angles are respectively switched based on a rapid simulation method and combined with an Archimedes intelligent optimization method, the initial attitude instruction of the missile is subjected to iterative calculation according to 0-180 degrees to obtain the maximum attack distance and the minimum attack distance launched at the moment, an optimal solution is obtained through an Archimedes intelligent optimization algorithm, and finally the initial attitude instruction reaching the maximum attack distance under different launching conditions is obtained. According to the flight characteristics of the high-speed aircraft, an Archimedes optimization algorithm is combined to solve an attack area, and the step of reversely solving an initial instruction signal of the aircraft specifically comprises the following steps:
step 31: establishing an Archimedes intelligent optimization algorithm model;
(2) initializing all object positions
Oi＝lbi+rand×(ubi-lbi)；i＝1,2,...,N (14)
In the formula, OiIs the ith object, lb, in the set of N objectsiAnd ubiLower and upper bounds of the search space, respectively;
initializing the volume vol of the ith object using equation (15)iAnd density deni：
Figure BDA0003526033900000064
Wherein rand is a D-dimensional vector and randomly generates [0, 1]]A number in between. Finally, the acceleration acc of the ith object is initializedi；
acci＝lbi+rand×(ubi-lbi)；i＝1,2,…,N (16)
(2) Updating the density and the volume;
the density and volume update formula for the ith object for the t +1 th iteration is:
Figure BDA0003526033900000061
wherein, volbestAnd denbestIs the volume and density of the best object found to date;
(3) defining a transfer operator and a density operator;
firstly, collision occurs between objects, after a period of time, the objects try to reach an equilibrium state, the collision is realized in the Archimedes algorithm through a transfer operator TF, the transfer operator TF converts the flow of the algorithm from an exploration mode to a development mode, and the definition of the transfer operator TF is as follows:
Figure BDA0003526033900000062
wherein the transfer operator TF increases gradually with time up to 1, where t and tmaxRespectively representing the current iteration times and the maximum iteration times, wherein similarly, a density factor d helps the algorithm to search from the global state to the local state, and d is reduced along with the increase of the iteration time;
Figure BDA0003526033900000063
(4) selecting an exploration mode;
if the transfer operator TF is less than or equal to 0.5, the objects collide, one object is randomly selected, and the acceleration of the object is updated for t +1 iterations by using a formula (20):
Figure BDA0003526033900000071
wherein deni,voliAnd acc ofiIs the density, volume and acceleration of the object i, and accmr,denmrAnd volmrAcceleration, density and volume of the random material;
(5) selecting a development mode;
if the transfer operator TF is larger than 0.5 and no collision occurs between the objects, updating the t +1 times of iterative acceleration of the objects by using a formula (21);
Figure BDA0003526033900000072
wherein, accbestIs the optimal acceleration of the object;
(6) normalizing the acceleration;
the acceleration of the object is normalized using equation (22) to calculate the percent change.
Figure BDA0003526033900000073
Where u and l are normalized ranges, setting the values of u and l to 0.9 and 0.1, respectively,
Figure BDA0003526033900000074
defining the percentage of steps that each individual will change, if the object is far from the global optimum, the acceleration value will be high, which means that the target will be in exploration mode; otherwise, in the development phase;
(7) updating the position;
(a) if TF is less than or equal to 0.5, namely the exploration phase, the position of the ith object in t +1 iterations is
Figure BDA0003526033900000075
In the formula, xrandIndividual positions randomly generated by the algorithm. C1Is a constant, which is assigned to 2 according to specific requirements;
(b) if TF > 0.5, the development phase, then the position of the ith object at t +1 iterations is
Figure BDA0003526033900000076
C2 is a constant, 6, T increases with time, proportional to the transfer operator, T 'C3 × TF, T' increases with iteration within the range [ C3 × 0.3, 1], initially taken as a percentage from the optimal position of the initial object;
in the formula (24), F is a mark of the motion direction of the object;
Figure BDA0003526033900000081
wherein, P2 rand-C4;
(8) evaluating;
evaluating each individual by using an objective function f, recording the best solution found, and distributing the individual x with the best fitnessbestOptimal density denbestOptimal volume volbestAnd an optimum acceleration accbest；
Step 32, solving a fire control instruction by combining an Archimedes intelligent optimization algorithm based on a rapid simulation method for fire control model solution;
the fitness function of the Archimedes algorithm is:
Figure BDA0003526033900000082
in the formula, V1-speed of the carrier, VM-target speed, theta-carrier speed declination, q-line-of-sight angle, thetaM-target velocity dip;
in the calculation process, for the flight state instruction of the aircraft at the attack distance iterated by using the rapid simulation method each time, the fitness value of each individual in the population is calculated according to the fitness function, the fitness value is returned to the Archimedes algorithm to iteratively update the position, the volume and the acceleration information of each individual, and the solved attack distance and the aircraft state instruction at the attack distance are output until the function reaches the allowable error or the algorithm reaches the maximum iteration times.
The invention has the beneficial effects that: according to the target task requirement of the fire control of a future high-speed aircraft, a fire control model of a hypersonic platform is respectively established, wherein the fire control model comprises a target motion prediction model, a missile outer trajectory model and a fire control hit problem solving model; solving an attack area by combining an Archimedes optimization algorithm according to the flight characteristics of the high-speed aircraft, and reversely solving an initial instruction signal of the aircraft; according to the fire control scheme, a high-speed aircraft is selected as a throwing aircraft, a novel intelligent optimization algorithm is combined with a traditional numerical integration method, fire control instructions of the aircraft are intelligently resolved, the intelligent decision of a fire control model is realized, the performance advantages of high speed and high maneuverability of the aircraft can be brought into play, the task execution efficiency is greatly improved, and the requirements of air fire control in the future and the development trend of the intellectualization of a fire control system are met; the method has few control parameters and better robustness, and can solve the optimization problem by generating the objective function value with the minimum error.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of the high-speed aircraft carrier throwing platform for executing the air-to-air task.
FIG. 3 is a flow chart of the solution of the fire control model equation set of the high-speed aircraft.
FIG. 4 is a flow chart of the problem solving process using the Archimedes algorithm of the present invention.
FIG. 5 is a schematic diagram of the overall process of solving the fire control command based on the Archimedes intelligent algorithm of the rapid simulation.
FIG. 6 is a schematic view of a missile attack zone obtained in the practice of the present invention.
Detailed Description
As shown in fig. 1, an intelligent solution method for a fire control model of a high-speed aircraft includes the following steps:
step 1: according to the flight characteristics of the high-speed aircraft platform, a high-speed aircraft motion equation on the rotating circular ground is deduced, and polynomial fitting of data is performed by using a polynomial proxy model structure according to the model data of the existing aircraft. After fitting, the fitted polynomial proxy model is subjected to model evaluation by using a goodness-of-fit test method.
Figure BDA0003526033900000091
Wherein SSR is the regression sum of squares of the data, SST is the sum of the introduced total squares, SSE is the sum of the squares of the errors of the data, and SST ═ SSE + SSR.
Step 2: and constructing a fire control model of the high-speed aircraft platform, wherein the fire control model comprises target motion prediction, a missile outer trajectory model and a fire control hit problem resolving model.
And establishing a target motion prediction model by using an interactive multi-model algorithm, namely decomposing the target motion state into a combination of multiple motion states.
And then establishing an outer ballistic model of the missile, wherein similarly, when the high-speed aircraft is used as a carrier launching platform, the high-speed aircraft is different from the traditional aircraft model, and the flight characteristics of the aircraft cause the initial launching speed and the initial launching height to be changed. Therefore, in the model establishment, it is necessary to consider the problems of the centrifugal acceleration due to the curvature of the earth and the coriolis acceleration due to the rotation, and therefore, it is necessary to establish a missile motion model in the rotating circular ground. As shown in FIG. 2, the equation of particle motion for a missile is as follows:
Figure BDA0003526033900000101
in the formula, r is the distance from the center of mass to the geocenter of the missile aircraft, theta is longitude, phi is latitude, V is the speed of the missile aircraft, gamma is the trajectory inclination angle, and psi is the trajectory deflection angle. X, D, L are thrust, resistance and lift force of the aircraft, g is the gravity acceleration of the local position of the aircraft, alpha is the angle of attack of the missile aircraft, sigma is the roll angle of the missile aircraft, omega iseIs the rotational angular velocity of the earth.
And finally, establishing a fire control hit problem solving model. In the air-to-air task executed by the high-speed aircraft, the throwing aircraft carrier platform is a reusable flight-push coupled high-speed aircraft, so that the maneuvering performance is excellent, the flight envelope is large, and the comprehensive performance of the platform is greatly improved compared with that of the traditional aircraft. The high performance of the platform can reduce the requirement of the object thrown on the platform compared with the object thrown on the traditional aircraft; for example, in the throwing process, the initial speed of the thrown projectile is very high, so that the thrown object can be unpowered, and an unpowered guidance mode can be considered, so that the throwing cost is reduced. According to the problem, the problem model of fire control hit is established as follows:
Figure BDA0003526033900000102
due to the high supersonic speed flight characteristic of the airborne platform, high requirements are put on the rapidity and the accuracy of throwing, and therefore a rapid simulation method is adopted for simulation in fire control launching.
Based on a rapid simulation calculation equation set in the established fire control model, under the determined initial condition, the maximum power range of the missile is used as an initial value of the distance to calculate the parameter change of each point of the missile in the attack process, and then the hit limit conditions such as hit miss amount and the like specified by the characteristics of the missile are used for judging whether the missile hits a target or not, if the missile does not hit the target, the miss amount is subtracted from the distance to be used as the initial value of the next calculation, and the maximum launching distance of the missile is obtained through the cycle calculation; and the minimum launching distance of the missile can be obtained in the same way. And the initial value is continuously changed for calculation, and finally the missile attack area can be obtained.
In addition, the method of changing the step length is adopted in the process of calculating the missile attack area with the smaller step length, and is an important measure for improving the operation speed and ensuring the completion of calculation. If the step is excessively obtained in the calculation, the calculation error is increased and even diverged, and particularly when the missile approaches to a target, when the distance in one step length delta t time is more than two times of the hit and miss amount, the misjudgment can be caused, the hit condition is judged as miss, and the calculated attack area boundary is not correct; conversely, if the step size is taken too small, the speed of the calculation will be affected. For the above reasons, integration is performed with variable step size in the program: when the calculation is started, a larger step length can be selected, and when the missile approaches or hits a target, a smaller step length is selected, so that the calculation speed can be greatly increased under the condition that the whole calculation meets a certain precision, and a specific flow chart is shown in fig. 3.
And step 3: establishing a system based on a rapid simulation method and combined with an Archimedes intelligent optimization method, respectively switching different initial missile launching line-of-sight angles, iteratively calculating the maximum attack distance and the minimum attack distance launched at the moment according to the initial attitude instruction of the missile from 0 degree to 180 degrees, obtaining an optimal solution through an Archimedes intelligent optimization algorithm, and finally obtaining the initial attitude instruction reaching the maximum attack distance under different launching conditions, as shown in fig. 4 and 5.
In the archimedes intelligent optimization algorithm, the volume and density of the object are updated every iteration:
Figure BDA0003526033900000111
wherein, volbestAnd denbestIs the volume and density of the best object found so far, and rand is a uniformly distributed random number.
When the transfer factor TF in the algorithm is less than or equal to 0.5, the object collides, the algorithm enters an exploration mode, and the acceleration updating formula of the object is as follows:
Figure BDA0003526033900000112
wherein deni,voliAnd acc ofiIs the density, volume and acceleration of object i, and accmr,denmrAnd volmrAcceleration, density and volume of the random material.
The position of the ith object at t +1 iterations is:
Figure BDA0003526033900000121
if the transfer operator TF is more than 0.5, the objects do not collide with each other, the algorithm enters a development mode, and the acceleration updating formula of the objects in the mode is as follows:
Figure BDA0003526033900000122
the location update formula of the ith object is:
Figure BDA0003526033900000123
the main advantage of the hypersonic vehicle platform is that fire control tasks can be performed at greater distances to the target. Therefore, in order to fully exert the performance characteristics of the airborne platform, the fitness function of the Archimedes algorithm is as follows:
Figure BDA0003526033900000124
the initial simulation conditions set by the invention are that the initial flying height of the aircraft is 23000m, the speed is 1180m/s (Ma is 4), and the average speed of the target in 10 seconds is 450 m/s. The angular velocity of a target tracked by the missile is limited to 20 degrees/s, a proportional guidance mode is adopted, K is 4, the missile is tracked by a radar of the missile, the maximum detection angle of a radar position marker of the missile is 2rad (114 degrees), so the absolute value of the angle of sight is limited to be less than 114 degrees, and the relative velocity required for destroying the target is 5 m/s. In the archimedes algorithm, the population size is set to be 30, the maximum number of iterations is set to be 1000, C1 is 2, C2 is 6, C3 is 2, and C4 is 0.5. Through preliminary simulation, considering the track drift angle reaching the maximum distance under different line-of-sight angles, the assumption is also adopted, and the target line-of-sight angle limit is less than 360 degrees, so that the following attack area taking the target as the center can be obtained as shown in fig. 6.
The maximum attack distance is found to appear at the position with the visual line angle of about 180 degrees instead, which shows that the high-speed aircraft can often carry out object launching in front of or far in front of the target when executing the air-space task, and the launching mode of over-shoulder launching is adopted, and the high-speed aircraft quickly breaks away from the high-maneuverability aircraft by the characteristics of high speed and high maneuverability of the aircraft after launching is finished. The fire control mode can better exert the extremely strong flight performance of the high-speed aircraft and greatly improve the survival capability of the aircraft.

Claims (6)

1. An intelligent resolving method of a fire control model of a high-speed aircraft is characterized by comprising the following steps:
step 1, establishing an agent model of a high-speed aircraft airborne launching platform considering flight-push coupling according to existing data;
step 2, constructing a fire control model of the high-speed aircraft platform, wherein the fire control model comprises a target motion prediction model, a missile outer trajectory model and a fire control hit problem resolving model;
and 3, solving an attack area by combining an Archimedes optimization algorithm according to the flight characteristics of the high-speed aircraft, and reversely solving an initial instruction signal of the aircraft.
2. The intelligent solution method for the fire control model of the high-speed aircraft according to claim 1, wherein in the step 1, establishing the agent model of the on-board launch platform of the high-speed aircraft considering the flight-thrust coupling according to the existing data specifically comprises the following steps:
step 11, assuming that the aircraft flies in the rotating spherical ground, deducing to obtain a nonlinear mathematical model of the high-speed aircraft in the rotating spherical ground;
and step 12, sampling data according to the aerodynamic data, the geometric parameters and the propulsion coefficient of the aircraft in the existing database, fitting a polynomial to the sampled hypersonic velocity section data, and performing model evaluation on the fitted polynomial proxy model by using a goodness-of-fit test method after fitting.
3. The intelligent calculation method for the fire control model of the high-speed aircraft according to claim 1, wherein in the step 2, the establishment of the target motion prediction model specifically comprises: predicting the target by adopting an interactive multi-model algorithm, and decomposing the motion mode of the target into the synthesis of the following motion state models:
(1) a CV model;
when the target does not move, namely does uniform linear motion or uniform acceleration linear motion, the following second-order constant-speed CV models are respectively adopted;
assuming that the target does uniform linear motion, the target displacement is recorded as x (t), and the speed is recorded as x (t)
Figure FDA0003526033890000011
Under the condition that random disturbance exists in the target speed, the speed random disturbance is assumed to obey that the mean value is zero and the variance is delta2White gaussian noise a (t);
taking system state variables
Figure FDA0003526033890000012
According to Newton's law of motion, there are
Figure FDA0003526033890000013
Written in matrix form as
Figure FDA0003526033890000014
I.e. CV model of
Figure FDA0003526033890000021
Wherein, A (t) is the system matrix of the model, and B (t) is the input matrix.
(2) A CT model;
when the target makes constant turning motion with constant speed and constant direction but changing moment, the CT model is used for describing, and the discrete time domain form of the CT model is expressed as follows:
Figure FDA0003526033890000022
in the formula, xkAnd ykThe position components of the target state in the cartesian coordinate system along the x-axis and y-axis directions at time k,
Figure FDA0003526033890000023
and
Figure FDA0003526033890000024
for the corresponding velocity component at time k,
Figure FDA0003526033890000025
and
Figure FDA0003526033890000026
for corresponding mean values of zero variance q2White noise in the Gaussian process, w is a constant turning rate and can reflect the maneuvering condition of a target, p is a radar sampling interval, and a state transition equation describes the recursion relation of the target state from the moment k to the moment k + 1;
(3) a Xinge model;
the Singer model is a first-order time correlation model with the acceleration mean value of zero, and assuming that the target maneuvering acceleration time correlation function is in an exponential decay form, the time correlation function Ra (τ) of the Singer model is as follows:
Figure FDA0003526033890000027
in the formula:
Figure FDA0003526033890000028
a is the undetermined parameter that determines the target maneuver characteristics within the interval (t, t + τ). a (t) is the acceleration of the maneuver,
Figure FDA0003526033890000029
is the maneuvering acceleration variance.
4. The intelligent calculation method for the fire control model of the high-speed aircraft according to claim 1, wherein in the step 2, the establishment of the missile outer ballistic model specifically comprises the following steps: when the high-speed aircraft is used as a carrier throwing platform, the establishment process of the fire control model is changed compared with the traditional model: the flight characteristics of the aircraft bring new requirements to the initial launching speed and the initial launching height, the launching height can be higher and is closer to the adjacent space, and the initial launching speed can be higher.
5. The intelligent calculation method for the fire control model of the high-speed aircraft according to claim 1, wherein in the step 2, the establishment of the fire control hit problem calculation model specifically comprises: the method adopts a rapid simulation method for simulation in fire control emission, and specifically comprises the following steps:
(1) the missile adopts a proportional guidance law, and the action of a control system is not considered;
(2) solving a motion differential equation set of the missile by using a rapid variable step length integration method;
(3) the program is optimally designed, and the operation speed is improved by means of structure modularization and the like;
establishing a mathematical model of the air-to-air guidance of the high-speed aircraft carrier throwing platform, and the visual angular velocity of the missile and the target
Figure FDA0003526033890000031
Is composed of
Figure FDA0003526033890000032
Rate of change of distance
Figure FDA0003526033890000033
Is composed of
Figure FDA0003526033890000034
Wherein, V1Speed of the carrier, VM-target speed, r-target distance, theta-vehicle speed slip angle, q-line-of-sight angle, thetaM-target velocity inclination angle, ηM-target heading angle, η -vehicle heading angle, q0Is an initial value of the line-of-sight angle between the missile and the target, r0The distance between the missile and the target is an initial value, and delta t is the target flight time;
the equation for the motion characteristic of the target is described by the following equation:
Figure FDA0003526033890000035
wherein T is the time of flight, θ, of the target timed at the missile launch instantM0Initial value of target velocity inclination angle, ηM0Initial value of target course angle, GMIs the subject of a mobile overload,
Figure FDA0003526033890000036
target rate of change of speed inclination, when GMWhen the value is 0, the target moves linearly at a constant speed, and when G is equal toMWhen not equal to 0, the target does constant-speed circular motion;
integrating the above equation to obtain:
Figure FDA0003526033890000037
wherein, thetaM0Initial value of target velocity inclination angle, ηM0-a target course angle initial value;
after the acceleration of the missile is integrated, the velocity value of the missile at any moment is obtained
Figure FDA0003526033890000041
In the formula, V0Is the initial velocity of the missile,
Figure FDA0003526033890000042
the missile speed change rate is shown.
The proportional guidance equation of the missile is
Figure FDA0003526033890000043
In the formula, K is a proportional guidance coefficient,
Figure FDA0003526033890000044
-rate of change of speed declination;
the motion of the target not only affects the motion characteristics of the target, but also affects the guidance law of the missile:
Figure FDA0003526033890000045
in the formula (I), the compound is shown in the specification,
Figure FDA0003526033890000046
is the rate of change of the line of sight angle.
The fire control model of the high-speed aircraft airborne delivery platform is as follows:
Figure FDA0003526033890000047
based on a rapid simulation calculation equation set in the established fire control model, under the determined initial condition, starting to calculate the parameter change of each point of the missile in the attack process by using the maximum power range of the missile as an initial value of the distance, judging whether the missile hits a target or not according to hit limiting conditions specified by missile characteristics such as hit miss amount and the like, if the missile does not hit the target, subtracting the miss amount from the distance as the initial value of the next calculation, and circularly calculating in such a way to finally obtain the maximum launching distance of the missile; in the same way, the minimum launching distance of the missile can be obtained, and the initial value q is continuously changed0Calculating to finally obtain a missile attack area;
integration is performed with varying step sizes in the program: when the calculation is started, a larger step length is selected, and when the missile approaches or hits a target, a smaller step length is selected, so that the calculation speed is greatly increased under the condition of meeting a certain precision.
6. The intelligent solution method for the fire control model of the high-speed aircraft according to claim 1, wherein in the step 3, the attack region is solved by combining an Archimedes optimization algorithm according to the flight characteristics of the high-speed aircraft, and the inverse solution of the initial command signal of the aircraft specifically comprises the following steps:
step 31: establishing an Archimedes intelligent optimization algorithm model;
(1) initializing all object positions
Oi＝lbi+rand×(ubi-lbi)；i＝1,2,...,N (14)
In the formula, OiIs the ith object, lb, in the set of N objectsiAnd ubiLower and upper bounds of the search space, respectively;
initializing the volume vol of the ith object using equation (15)iAnd density deni：
Figure FDA0003526033890000051
Wherein rand is a D-dimensional vector and randomly generates [0, 1]]And finally, the acceleration acc of the ith object is initializedi；
acci＝lbi+rand×(ubi-lbi)；i＝1,2,...,N (16)
(2) Updating the density and the volume;
the density and volume update formula for the ith object for the t +1 th iteration is:
Figure FDA0003526033890000052
wherein, volbestAnd denbestIs the volume and density of the best object found so far, and rand is a uniformly distributed random number;
(3) defining a transfer operator and a density operator;
firstly, collision occurs between objects, after a period of time, the objects try to reach an equilibrium state, and the collision is realized in an Archimedes algorithm through a transfer operator TF, the transfer operator TF converts the flow of the algorithm from an exploration mode to a development mode, and the definition of the transfer operator TF is as follows:
Figure FDA0003526033890000053
wherein the transfer operator TF increases gradually over time up to 1, where t and tmaxRespectively representing the current iteration times and the maximum iteration times, wherein similarly, a density factor d helps the algorithm to search from the global state to the local state, and d is reduced along with the increase of the iteration time;
Figure FDA0003526033890000054
(4) selecting an exploration mode;
if the transfer operator TF is less than or equal to 0.5, the object collides, one object is randomly selected and the acceleration of the object is updated for t +1 iterations by using a formula (20):
Figure FDA0003526033890000061
wherein deni,voliAnd acc ofiIs the density, volume and acceleration of object i, and accmr,denmrAnd volmrAcceleration, density and volume of the random material;
(5) selecting a development mode;
if the transfer operator TF is larger than 0.5 and no collision occurs between the objects, updating the t +1 iterative acceleration of the objects by using a formula (21);
Figure FDA0003526033890000062
wherein, accbestIs the optimal acceleration of the object;
(6) normalizing the acceleration;
normalizing the acceleration of the object using equation (22) to calculate a percent change;
Figure FDA0003526033890000063
where u and l are normalized ranges, setting the values of u and l to 0.9 and 0.1, respectively,
Figure FDA0003526033890000064
defining the percentage of steps that each individual will change, if the object is far from the global optimum, the acceleration value will be high, which means that the target will be in exploration mode; otherwise, in the development phase;
(7) updating the position;
(a) if TF is less than or equal to 0.5, namely the exploration phase, the position of the ith object in t +1 iterations is
Figure FDA0003526033890000065
In the formula, xrandAre individual positions randomly generated by the algorithm. C1Is a constant and is assigned to 2 according to specific requirements;
(b) if TF > 0.5, the development phase, then the position of the ith object at t +1 iterations is
Figure FDA0003526033890000066
C2 is a constant, 6, T increases with time, proportional to the transfer operator, T ═ C3 × TF, T increases with iteration within the range [ C3 × 0.3, 1], initially taking a certain percentage from the optimal position of the initial object;
in the formula (24), F is a mark of the motion direction of the object;
Figure FDA0003526033890000071
wherein, P2 rand-C4;
(8) evaluating;
evaluating each individual by using an objective function f, recording the best solution found, and distributing the individual x with the best fitnessbestOptimum density denbestOptimal volume volbestAnd an optimum acceleration accbest；
Step 32, solving a fire control instruction by combining an Archimedes intelligent optimization algorithm based on a rapid simulation method for fire control model solution;
the fitness function of the Archimedes algorithm is as follows:
Figure FDA0003526033890000072
in the calculation process, for the flight state instruction of the aircraft at the attack distance iterated by using the rapid simulation method each time, the fitness value of each individual in the population is calculated according to the fitness function, the fitness value is returned to the algorithm to iteratively update the position, the volume and the acceleration information of each individual, and the solved attack distance and the aircraft state instruction at the attack distance are output until the function reaches the allowable error or the algorithm reaches the maximum iteration times.
CN202210196520.9A 2022-03-01 2022-03-01 Intelligent resolving method for fire control model of high-speed aircraft Pending CN114662285A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210196520.9A CN114662285A (en) 2022-03-01 2022-03-01 Intelligent resolving method for fire control model of high-speed aircraft

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210196520.9A CN114662285A (en) 2022-03-01 2022-03-01 Intelligent resolving method for fire control model of high-speed aircraft

Publications (1)

Publication Number Publication Date
CN114662285A true CN114662285A (en) 2022-06-24

Family

ID=82027736

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210196520.9A Pending CN114662285A (en) 2022-03-01 2022-03-01 Intelligent resolving method for fire control model of high-speed aircraft

Country Status (1)

Country Link
CN (1) CN114662285A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115221801A (en) * 2022-09-20 2022-10-21 中国人民解放军国防科技大学 Aircraft uncertainty propagation analysis method and device based on dynamic approximate modeling

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115221801A (en) * 2022-09-20 2022-10-21 中国人民解放军国防科技大学 Aircraft uncertainty propagation analysis method and device based on dynamic approximate modeling
CN115221801B (en) * 2022-09-20 2022-12-09 中国人民解放军国防科技大学 Aircraft uncertainty propagation analysis method and device based on dynamic approximate modeling

Similar Documents

Publication Publication Date Title
US8038062B2 (en) Methods and apparatus for path planning for guided munitions
CN109254591B (en) Dynamic track planning method based on Anytime restoration type sparse A and Kalman filtering
US20080206718A1 (en) Apparatus, method and computer program product for weapon flyout modeling and target damage assessment
CN113342047A (en) Unmanned aerial vehicle path planning method for improving artificial potential field method based on obstacle position prediction in unknown environment
CN114840020A (en) Unmanned aerial vehicle flight path planning method based on improved whale algorithm
Li et al. Autonomous maneuver decision-making for a UCAV in short-range aerial combat based on an MS-DDQN algorithm
CN113093733B (en) Sea-to-sea striking method for unmanned boat cluster
CN113625740A (en) Unmanned aerial vehicle air combat game method based on transfer learning pigeon swarm optimization
CN114035616B (en) Method and system for controlling striking of aircraft to moving target
CN114462293B (en) Hypersonic speed target medium-long term track prediction method
CN114662285A (en) Intelligent resolving method for fire control model of high-speed aircraft
CN114675673A (en) Aerial moving target tracking method and system
Moore Radar cross-section reduction via route planning and intelligent control
Gaudet et al. Terminal adaptive guidance for autonomous hypersonic strike weapons via reinforcement learning
Zhuang et al. Optimization of high-speed fixed-wing UAV penetration strategy based on deep reinforcement learning
CN116011315A (en) Missile escape area fast calculation method based on K-sparse self-coding SVM
CN114967735A (en) Multi-UCAV collaborative real-time track planning method
CN112949150A (en) Variable structure-based adaptive multi-model box particle filter ballistic target tracking method
CN114200439A (en) Multi-mode airspace target tracking method based on Doppler blind area
Zeng et al. Positioning and Tracking Performance Analysis of Hypersonic Vehicle based on Aerodynamic Model
Kaplan et al. The analysis of a generic air-to-air missile simulation model
CN116992553B (en) Whole-course trajectory estimation method of boosting gliding aircraft
Zhang et al. Intelligent Close Air Combat Design based on MA-POCA Algorithm
Zeng et al. Positioning and Tracking Performance Analysis of Hypersonic Vehicle Based on Cubature Kalman Filter
Chen et al. Optimal Guidance Method for UCAV in Close Free Air Combat

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination