CN115033025B - Situation cognition result-based track guarantee method - Google Patents
Situation cognition result-based track guarantee method Download PDFInfo
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- CN115033025B CN115033025B CN202210950059.1A CN202210950059A CN115033025B CN 115033025 B CN115033025 B CN 115033025B CN 202210950059 A CN202210950059 A CN 202210950059A CN 115033025 B CN115033025 B CN 115033025B
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Abstract
The invention discloses a track guarantee method based on situation cognition results, which adopts an ant colony algorithm, starts from the situation cognition results of confrontation, completes state deduction in the confrontation process, obtains real-time performance parameters, performs track guarantee design on an aircraft from 3 aspects of confrontation situation analysis, aircraft threat degree analysis and track generation, and ensures that the aircraft completes flight tasks on the premise of self safety guarantee. According to the method, the threat suffered by the aircraft in the confrontation is analyzed to obtain the threat capability model, the threat range and the threat value suffered by the aircraft are obtained, the generation of the flight path of the aircraft is realized according to the analysis result, and the lowest threat suffered by the aircraft flying according to the flight path is ensured.
Description
Technical Field
The invention belongs to the field of radar countermeasure, and particularly relates to a track guarantee method based on situation cognition results.
Background
With the rapid development of modern science and technology and information technology, the sudden increase of the countermeasure, the change and the process of the countermeasure situation are accelerated, and higher requirements are put forward on the timeliness and the flexibility of the countermeasure. The aircraft has the characteristics of high speed, strong penetration resistance, flexible and variable tactics and the like, and particularly, the appearance of the aircraft with a stealth function and the arrangement of powerful weapons make the aircraft become an outstanding chief role in modern countermeasures. However, due to the increasing comprehensiveness of modern countermeasures, various sophisticated devices emerge endlessly, and particularly, the continuous development of radar technology, so that the aircraft is increasingly threatened in the countermeasures. Therefore, how to guarantee the survival probability and the task execution efficiency of the aircraft in practical countermeasures has become one of the important concerns of many researchers today, and one of the more effective methods is the track guarantee design. The flight path guarantee design is that through information fusion, attribute information and confrontation related situation information of a flight plan about an aircraft can be fully utilized, and parameters such as a flight path, a flight course, a speed, an altitude and time of the aircraft are determined in advance or temporarily, so that a planning task is completed on the premise of guaranteeing the safety of the aircraft.
The track guarantee design of the aircraft is actually to obtain quantitative description of a flight track safety threshold value according to the calculation of the direction, the speed, the height, the position and the threat degree of the aircraft on a flight line, and convert the track design problem into a track optimization problem. Therefore, researchers at home and abroad propose corresponding algorithms, and the algorithms generally use a numerical solution algorithm with optimal path to obtain the optimal path by solving the most value of relevant functions of flight paths. However, the algorithms have strict requirements on solving conditions, lack universality, lack dynamic analysis on the threats and have poor applicability.
Disclosure of Invention
The invention provides a track guarantee method based on situation cognition results, which starts from confrontation situation cognition results, is based on an ant colony algorithm, and performs track guarantee design on an aircraft from 3 aspects of confrontation situation analysis, aircraft threat degree analysis and track generation, thereby ensuring that the aircraft completes flight tasks under the premise of self safety guarantee.
The technical solution for realizing the invention is as follows: a track guarantee method based on situation cognition results comprises the following steps:
step 1, constructing a confrontation situation analysis simulation platform, wherein the confrontation situation analysis simulation platform comprises a radar model, a communication model, an electronic interference model, an electronic reconnaissance model, an airplane/ship model, an environment model and a weapon equipment model, establishing confrontation relations among equipment models in the flight process of the aircraft through the radar model, the communication model, the electronic interference model, the electronic reconnaissance model, the airplane/ship model, the environment model and the weapon equipment model, and taking the confrontation relations as data sources for various calculations and evaluations in the subsequent track guarantee design, and turning to step 2.
Step 2, establishing a time sequence simulation module according to control parameters of the confrontation situation analysis simulation platform, generating a situation simulation working time sequence, providing various triggering and synchronizing signals for each model in the simulation platform, providing the time sequence and the control signals of each model in the signal processing interior, and turning to step 3.
And 3, simulating and deducing by the confronting situation analysis simulation platform according to the confronting relation among the equipment models established in the step 1 and the situation simulation working time sequence generated in the step 2, evaluating the networking radar detection distance of the aircraft based on simulation situation cognition, determining the probability of the aircraft discovered by the radar, obtaining a radar threat value, and turning to a step 4.
And 4, calculating the comprehensive threat degree of the aircraft for each grid point of the confrontation space to obtain the comprehensive threat degree value of each grid point, and turning to the step 5.
And 5, carrying out optimal track solution according to the comprehensive threat values of the grid points to realize track planning:
and during the course planning, deduction is carried out according to the confrontation scene, the influence range and the threat degree aiming at the aircraft threat in the deduction are obtained, the mutual influence of the course route and the threat is comprehensively considered, and a safe course is formed.
Compared with the prior art, the invention has the remarkable advantages that: aiming at the problem of flight path guarantee of an aircraft in modern confrontation, the flight path guarantee design method adopts an ant colony algorithm and plans the flight path by utilizing a situation cognitive result. The track guarantee design method based on the situation cognition result takes the threat of radar equipment to an aircraft in the countermeasure as a reference factor, divides the countermeasure space by grids, carries out real-time deduction analysis aiming at the threat in the countermeasure, integrates and calculates the comprehensive threat of each grid point, takes the threat range and the threat value of each grid point as reference quantities, introduces an pheromone function to be fully considered, and obtains the solution of the optimal flight track. Under the existing condition, the optimal route design with safety guarantee can be effectively realized.
Drawings
FIG. 1 is a flow chart of the operation of the confrontational situation simulation platform of the present invention.
Fig. 2 is a schematic diagram of a space-based networking radar transmitting-receiving split cooperative detection mode.
Fig. 3 is a flow chart of the flight path guarantee design of the aircraft based on the ant colony algorithm.
FIG. 4 is an optimal flight path diagram for an aircraft path assurance design.
FIG. 5 is a flow chart of the track support method based on situational awareness results according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without inventive step, are within the scope of the present invention.
The following further introduces specific embodiments, technical difficulties and inventions of the present invention with reference to the design examples.
With reference to fig. 1 to 5, the method for track support based on situational awareness results according to the present invention includes the following steps:
step 1, constructing a confrontation situation analysis simulation platform. The adversity analysis is the basis of the flight path guarantee design of the aircraft and aims to carry out adversity deduction and simulation evaluation. The confrontation situation analysis simulation platform adopts equipment models including a radar model, a communication model, an electronic interference model, an electronic reconnaissance model, an airplane/ship model, an environment model and a weapon equipment model according to simulation parameters, establishes confrontation relations among equipment in the flight process of the aircraft through the models, and is used as a data source for calculating and evaluating various items in subsequent track guarantee design, and the reliability, completeness and effectiveness of the subsequent design are determined by the accuracy of analysis.
The confrontation situation simulation is used as a complex, in order to ensure the comprehensive and accurate analysis of the threat degree of the aircraft, radar, communication, electronic interference, electronic reconnaissance, airplane/ship, environment and weapon equipment models are applied, and almost all the elements for constructing the confrontation simulation are included. In situation simulation, the requirements for the simulation model are multi-directional, including functionality, flexibility, and realism.
Functionality: the simulation model adopts a model form adapted to different simulation deduction schemes or strategies and applies different simulation time step length and coarse/fine granularity simulation functions.
Flexibility: the simulation model automatically matches the simulation processing flow and algorithm in the model according to the requirements of dynamic deduction, adopts the simulation functions of different deduction types of the same equipment model, and realizes flexible and configurable situation simulation.
Authenticity: the simulation model comprehensively considers the actual confrontation condition, the simulation calculation conforms to the actual equipment processing flow, and the situation result is described in a quantitative mode.
And 2, establishing a time sequence simulation module according to the control parameters of the simulation platform, generating a situation simulation working time sequence, and keeping the situation simulation working time sequence consistent with the actual situation. And providing various trigger and synchronous signals for each model in the simulation platform, and providing the time sequence and control signals of each model in the signal processing. The specific functions and procedures are as follows:
step 2-1), the time sequence simulation module is communicated with each model in the confrontation situation analysis simulation platform, the current simulation time is sent, and the step 2-2) is carried out;
step 2-2), judging whether the model receives the simulation time, if the model receives the simulation time, returning to the state of the model, starting to execute the operation of the current simulation time, and turning to the step 2-3); if the model does not receive the simulation time of the time sequence simulation module, the model stops working;
and 2-3) judging whether the time sequence simulation module receives the return state of a certain model, if not, waiting, and if not, determining that the model has a fault and reports the fault, issuing a simulation closing command, and forcibly terminating the simulation operation after the set waiting time duration is exceeded and the state information is not received.
The counter situation simulation processing flow is shown in fig. 1 according to various requirements of simulation.
And 3, carrying out simulation deduction on the countermeasure situation analysis simulation platform according to the countermeasure relation among the equipment models established in the step 1 and the situation simulation working time sequence generated in the step 2, and carrying out networking radar detection distance evaluation on the aircraft based on simulation situation cognition. In the countermeasure, the most effective measure is to reduce the probability of the aircraft being discovered if the survival probability of the aircraft is to be improved. As an apparatus for effectively detecting a target, radar is widely used in countermeasure. Even under a complex countermeasure environment, the modern radar can also rapidly and accurately detect and track a target, so that the safety of an aircraft is seriously influenced, and the threat of the aircraft flight is a main threat, so that the threat assessment of the aircraft based on situation cognition mainly takes radar threat as a main cause. The radar threats can be divided into fixed position radar threats and maneuvering radar threats according to radar states, wherein the fixed position radar has small variation of parameters such as position and environment, the detection capability and range are usually kept unchanged, and therefore the threat degree is relatively definite. The maneuvering radar, especially the space-based radar, has strong maneuvering capability, and often utilizes a transceiving split-location mode to cooperatively detect, so that the threat to the detection of the aircraft is greatly increased, and key analysis is needed.
The space-based networking radar mainly utilizes the theory that the appearance and the flying posture of an aircraft have influence on the scattering sectional area of the radar, and the probability of finding a target is improved by receiving signals through a plurality of radars. Theoretical research and experiments show that when electromagnetic waves irradiate different parts of an aircraft, such as the forward direction, the lateral direction and the backward direction, the radar scattering sectional areas corresponding to the aircraft can generate differences, radar signals reflected by different parts can be obtained by utilizing a multi-radar cooperative detection mode, so that the influence caused by the fact that the radar scattering sectional areas of the aircraft can change along with the difference of appearance and flight attitude is avoided, and a space-based networking radar receiving and transmitting split cooperative detection mode is provided in fig. 2. The scattering characteristic of the air-based networking radar can be calculated by the included angle between the flight attitude angle of the aircraft and the antennas for transmitting and receiving the radar, and at the moment, the equation of the double-base networking radar can be expressed as follows:
in the formula, G 1 For transmitting radar antenna gain, G 2 For receiving radar antenna gain, λ is radar signal wavelength, σ is aircraft radar cross-sectional area, SNR min To minimize the detectable Signal-to-noise ratio, R 1 For the distance between the aircraft and the transmitting radar, R 2 For the distance between the aircraft and the receiving radar, the following requirements are met:
-R 12 ≤R 1 -R 2 ≤R 12 ，R 1 +R 2 ≥R 12 (2)
in the formula, R 12 Is the distance between the transmitting radar and the receiving radar. When the networking radar adopts the A-sending-B-receiving mode, the distance R is detected d Can be expressed as:
in the formula, R dn The detection range of the nth radar when it operates alone is represented by a, which represents the number of transmitting radars, and B represents the number of receiving radars.
And 4, calculating the comprehensive threat degree of the aircraft for each grid point of the confrontation space. The design of the flight path guarantee of the aircraft is to plan the optimal flight path of the flight on the basis of comprehensively considering the performance and the threat degree of the aircraft, so that the aircraft can safely complete task execution, and therefore the threat degree distribution in the space needs to be evaluated and calculated.
4-1) spatially meshing the confrontation space.
4-2) calculating corresponding radar threat degrees at the grid points to obtain radar threat degree values of all the grid points, wherein the expression is as follows:
in the formula, gamma rni For the threat value, μ, of the nth radar of the ith grid point 1 、μ 2 、μ 3 、μ 4 、μ 5 The weighted values of the corresponding threat degrees of the distance, the speed, the azimuth angle, the speed change and the azimuth change, R dnmax Maximum detection distance, R, of nth radar dnmin Is the minimum detection distance, R, of the nth radar i Is the distance, Δ v, from the ith grid point to the nth radar ni The difference in speed, deltav, between the aircraft at the ith grid point and the nth radar max Is the maximum value of the speed difference, Δ a vni Difference in speed, Δ a, between the aircraft at the i-th grid point and the n-th radar vmax Is the maximum value of the speed variation difference, delta alpha ni Is the azimuth difference between the aircraft at the ith grid point and the nth radar, delta alpha max Is the maximum value of the azimuth difference, Δ a αni Difference in azimuth change, Δ a, between the aircraft at the i-th grid point and the n-th radar αmax Is the maximum value of the azimuth variation difference.
4-3) calculating the corresponding comprehensive threat degrees of all grid points according to the situation deduction to obtain the comprehensive threat degree value of each grid point, wherein the expression is as follows:
in the formula, gamma ri Is the integrated threat value, η, of the ith grid point n Weighting of nth radar threat obtained from radar detection capabilityThe value N is the number of threatened radars for the ith mesh point.
And 5, planning a flight path by using the comprehensive threat values of the grid points obtained in the step 4. When the flight path is planned, the algorithm deduces according to the confrontation scene, obtains the influence range and the threat degree aiming at the aircraft threat in deduction, comprehensively considers the mutual influence of the flight path and the threat, and forms a safe flight path. Because the threats of the aircrafts in the countermeasure are various, various threats can be mutually superposed, and the flight path planning analysis is relatively complex, the method adopts the ant colony algorithm to solve the optimal flight path.
The ant colony algorithm is a method for solving the optimization problem by utilizing the optimizing capability of the ant colony in the process of searching food sources, has parallelism and random searching property, and can obtain the optimal solution through the colony evolution process. For the problem of flight path guarantee planning, the method adopts the comprehensive threat degree value of each grid point obtained in the step 4 as a data basis of the ant colony algorithm. Generating initial pheromones according to the comprehensive threat degree of the aircraft flying through a flight planning track in sequence:
in the formula, w i The probability that the flight path passes through the ith grid point is planned for the flight in the initial population, E is a fixed constant, epsilon c Is the pheromone constant.
Subsequently, a transition probability q is generated using the pheromone i ：
In the formula, epsilon i Is the ith grid point pheromone, and M is the number of pheromones.
Selecting the next node according to the transition probability, recording the visited nodes, completing the visit of all the nodes, calculating the threat degree of the current flight path planning scheme, and then modifying the planning flight path according to the pheromone updating equation (8)Intensity of pheromone tracing through grid points
Wherein ρ is a pheromone attenuation coefficient,
indicating the intensity of the pheromone at the ith grid point.
And finally, repeatedly performing iterative computation, and outputting an optimal solution to obtain an optimal flight planning track. The aircraft track guarantee design flow based on the ant colony algorithm is shown in fig. 3.
Claims (3)
1. A track guarantee method based on situation cognition results is characterized by comprising the following steps:
step 1, constructing a confrontation situation analysis simulation platform, wherein the confrontation situation analysis simulation platform comprises a radar model, a communication model, an electronic interference model, an electronic reconnaissance model, an airplane/ship model, an environment model and a weapon equipment model, establishing confrontation relations among equipment models in the flight process of an aircraft through the radar model, the communication model, the electronic interference model, the electronic reconnaissance model, the airplane/ship model, the environment model and the weapon equipment model, and taking the confrontation relations as data sources for various calculations and evaluations in subsequent track guarantee design, and turning to step 2;
step 2, establishing a time sequence simulation module according to control parameters of the confrontation situation analysis simulation platform, generating a situation simulation working time sequence, keeping the situation simulation working time sequence consistent with the actual situation, providing various triggering and synchronizing signals for each model in the simulation platform, providing the time sequence and the control signals of each model in the signal processing, and turning to step 3;
step 3, the confrontation situation analysis simulation platform carries out simulation deduction according to the confrontation relation among the equipment models established in the step 1 and the situation simulation working time sequence generated in the step 2, carries out networking radar detection distance evaluation on the aircraft based on simulation situation cognition, determines the probability of the aircraft discovered by radar, obtains a radar threat value, and shifts to a step 4;
step 4, calculating the comprehensive threat degree of the aircraft for each grid point of the countermeasure space to obtain the comprehensive threat degree value of each grid point, which is as follows:
4-1) carrying out space gridding division on the confrontation space;
4-2) calculating corresponding radar threat degrees at each grid point to obtain radar threat degree values of each grid point, wherein the expression is as follows:
in the formula, gamma rni Is the threat value, mu, of the nth radar of the ith grid point 1 、μ 2 、μ 3 、μ 4 、μ 5 The weighted values of the corresponding threat degrees of the distance, the speed, the azimuth angle, the speed change and the azimuth change, R dnmax Maximum detection range, R, of nth radar dnmin Minimum detection distance, R, of nth radar i Is the distance, Δ v, from the ith grid point to the nth radar ni Is the speed difference between the aircraft at the ith grid point and the nth radar, deltav max Is the maximum value of the speed difference, Δ a vni Difference in speed, Δ a, between the aircraft at the ith grid point and the nth radar vmax For maximum difference in velocity, Δ α ni Is the azimuth difference between the aircraft and the nth radar at the ith grid point, delta alpha max Is the maximum value of the azimuth difference, Δ a αni Difference in azimuth change, Δ a, between the aircraft at the ith grid point and the nth radar αmax Is the maximum value of the azimuth variation difference;
4-3) calculating the corresponding comprehensive threat degrees of all grid points according to the situation deduction to obtain the comprehensive threat degree value of each grid point, wherein the expression is as follows:
in the formula, gamma ri Is the integrated threat value, η, of the ith grid point n Obtaining an nth radar threat degree weighted value according to radar detection capacity, wherein N is the number of threatened radars at an ith grid point;
turning to step 5;
step 5, carrying out optimal track solution according to the comprehensive threat values of the grid points to realize track planning:
when the flight path planning is carried out, deduction is carried out according to the confrontation scene, the influence range and the threat degree aiming at the aircraft threat in the deduction are obtained, the mutual influence of the flight path and the threat is comprehensively considered, and a safe flight path is formed;
the ant colony algorithm is adopted when the optimal flight path is solved, and the method specifically comprises the following steps:
and taking the comprehensive threat degree value of each grid point as a data basis of an ant colony algorithm, and generating initial pheromones according to the comprehensive threat degree suffered by the aircraft flying through a flight planning track in sequence:
in the formula, w i The probability of the flight path passing through the ith grid point is planned for the flight in the initial population, E is a fixed constant, epsilon c Is the pheromone constant;
subsequently, a transition probability q is generated using the pheromone i ：
In the formula, epsilon i Is the ith grid point pheromone, and M is the number of pheromones;
selecting the next node according to the transition probability, recording the accessed nodes, completing the access of all the nodes, and calculating the current flight path planningThe threat level of the scheme is changed, and then the intensity of the pheromone of the planned flight path passing through the grid points is modified according to the pheromone updating formula (8)
Where ρ is the pheromone attenuation coefficient,
intensity of pheromone representing the ith grid point;
and finally, repeatedly carrying out iterative computation and outputting an optimal solution, namely an optimal track.
2. The situation awareness result-based track support method according to claim 1, wherein: in step 2, according to the control parameters of the simulation platform, a timing sequence simulation module is established, a situation simulation working timing sequence is generated and is consistent with the actual situation, various trigger and synchronous signals are provided for each model in the simulation platform, and the timing sequence and the control signals of each model are provided for the interior of signal processing, which specifically comprises the following steps:
step 2-1), the time sequence simulation module is communicated with each model in the confrontation situation analysis simulation platform, the current simulation time is sent, and the step 2-2) is carried out;
step 2-2), judging whether the model receives the simulation time, if the model receives the simulation time, returning to the state of the model, starting to execute the operation of the current simulation time, and turning to the step 2-3); if the model does not receive the simulation time of the time sequence simulation module, the model stops working;
and 2-3) judging whether the time sequence simulation module receives the return state of a certain model, if not, waiting, and if the time sequence simulation module still does not receive the return state of the certain model, and if the time length of the waiting exceeds the set waiting time length, still not receiving the state information, considering that the model has a fault, reporting, issuing a simulation closing command, and forcibly terminating the simulation operation.
3. The situation awareness result-based track support method according to claim 1, wherein: in step 3, when the bistatic networking radar is adopted, the bistatic networking radar equation is expressed as follows:
in the formula, G 1 For transmitting radar antenna gain, G 2 For receiving radar antenna gain, λ is radar signal wavelength, σ is aircraft radar cross-sectional area, SNR min For minimum detectable signal to noise ratio, R 1 For the distance between the aircraft and the transmitting radar, R 2 For the distance between the aircraft and the receiving radar, the following requirements are met:
-R 12 ≤R 1 -R 2 ≤R 12 and R is 1 +R 2 ≥R 12
In the formula, R 12 For the distance between the transmitting radar and the receiving radar, when the networking radar adopts the A-transmitting and B-receiving mode, the distance R is detected d Expressed as:
in the formula, R dn The detection range of the nth radar when it operates alone is represented by a, which represents the number of transmitting radars, and B represents the number of receiving radars.
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