CN108445755A - Electronic jammers spatial domain based on refined Hook Jeeves algorighm delineates method - Google Patents
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Abstract
The invention discloses a kind of, and the electronic jammers spatial domain based on refined Hook Jeeves algorighm delineates method, belongs to electronic jammers spatial domain and delineates technical field.Purpose is that the optimal spatial domain delineating model of electronic jammers is established on the basis of radar coverage, airline safety interval and effective interference time under providing electronic interferences, and optimal spatial domain datum mark is found using refined Hook Jeeves algorighm.To avoid being absorbed in local optimum, linear regulation parameter is changed to Nonlinear Adjustment parameter in primal algorithm, and is introduced into the memory function in particle cluster algorithm, improves primal algorithm.Emulation shows that refined Hook Jeeves algorighm has more superiority than original optimization algorithm and particle cluster algorithm, can quickly and efficiently find optimal spatial domain datum mark, to delineate out the optimal spatial domain of electronic jammers to complete anti-task of specifically dashing forward.
Description
Technical Field
The invention relates to an improved optimization algorithm-based electronic jammer airspace planning method, and belongs to the technical field of electronic jammer airspace planning.
Background
In modern war, radar networking of enemies has become the killer mace in the fight against my warplane. The radar net has the characteristics of multiple systems, high precision and omnibearing detection, so that the fighter plane with excellent stealth performance and maneuvering performance is difficult to realize safety defense. In a novel combat operation, in order to achieve a specific combat purpose, a warplane performing a penetration task often needs to cooperate with an electronic interference plane, that is, the electronic interference plane emits an interference signal outside the fire attack of an enemy, so that a safety area is formed for the penetration fighter, and the enemy radar detection is avoided, so that how to reasonably and efficiently divide an airspace of the electronic interference plane becomes one of the problems that a commander needs to solve urgently. In supporting interference from a long distance, the conventional literature focuses mainly on the problem of interference resource allocation, and there are relatively few studies on how to partition the space of the jammer. The method is characterized in that rest anns and the like research the configuration problem of a radar jammer when a fixed target is shielded, Qiwei and the like propose a basic principle for supporting selection of a jammer position and planning of a flight line, Huangying researches the influence of the selection of the jammer position on the maximum detection distance of the radar from the aspects of distance, direction and height, Roughtao and the like propose basic requirements of electronic jammer airspace configuration, but airspace planning is not combined with specific tasks, and the prior art documents deeply research the configuration problem of the electronic jammer in cooperative combat, but think that the position of the jammer cooperative combat is fixed and the airspace planning is not combined with the actual flying of the jammer.
Disclosure of Invention
Therefore, aiming at the problems in the prior art, the invention aims to solve the problem of the airspace division of the jammer in the cooperative penetration process, aims to efficiently and flexibly use the airspace, shields the security penetration of the fighter, establishes an airspace division model of the jammer by taking the safety interval between the fighter and a radar threat center and the penetration route as a target function, and searches the optimal airspace reference point by adopting an improved optimization algorithm.
The technical scheme of the invention is as follows:
an improved optimization algorithm-based electronic jammer airspace planning method specifically comprises the following steps:
step 1: determining the number of initial airspace reference points, the maximum iteration number, the dimension, an upper bound and a lower bound according to an airspace reference point model of an interference machine, adjusting parameters and initializing the parameters, wherein t is 1;
step 2: randomly selecting initial airspace reference points, and calculating the safe course interval of each airspace reference point;
and step 3: whether the population meets three constraints is judged,
constraint 1: self-safety constraint of the jammer: that is, the airspace where the jammer is located must be outside the detection range of each radar;
constraint 2: commanding and controlling area constraint: namely, the airspace of the jammer must be within the command control area of the early warning machine of one party;
constraint 3: safety constraint of the defense fighter: that is, the safety interval of the flight path formed after the interference must meet the minimum safety interval of the flight path required by the fighter plane;
if not, the fitness is made negative infinity, the step 2 is returned, otherwise, the fitness value of each population is calculated according to a formula I, and the optimal fitness value of the third group before the fitness arrangement and the corresponding airspace reference point thereof are recorded, namely α and delta;
wherein d isiThe safety interval between the outburst prevention air route and the ith threat radar air route is suppressed; lambda [ alpha ]1Weight, λ, representing the safe interval of the flight path2Jammer representation and radarWeight of center point of the network, and λ1+λ2＝1；xj0,yj0The horizontal and vertical coordinates of the spatial reference point of the jth interference machine;
step 4, making t equal to t + 1;
step 5, updating according to a formula two, a formula three and a formula four respectively
Where t represents the current number of iterations,andis a vector of co-ordinated coefficients,in order to adjust the parameters of the device,andis random [0,1 ]]The vector of (1);
step 6, updating α positions and delta positions respectively according to a formula five, a formula six and a formula seven;
and 7: according to the formula eight, updating the position of the airspace reference point;
wherein,is [0,1 ]]Random number of (1), c1To adjust the coefficients.Is the best position point historically passed;
and 8: and (4) judging whether the maximum iteration times is reached, if so, finishing the algorithm and outputting an optimal result, otherwise, returning to the step (4).
Further, in the method, in the step 3, constraint 1, constraint 2 and constraint 3 are respectively judged according to a formula ten, a formula eleven and a formula twelve;
xj∈[xmin,xmax],yj∈[ymin,ymax]formula eleven
di≥dminAnd a formula of twelve.
The method has the technical effects that aiming at the problem that the algorithm is easy to fall into local optimization, the method for dividing the airspace of the electronic jammer based on the improved optimization algorithm changes linear adjustment parameters into nonlinear adjustment parameters, introduces a memory function in the particle swarm algorithm, and balances the problem that the iteration times are increased due to the adoption of the nonlinear adjustment parameters. And finally, in order to verify the effectiveness of the established model and improve the superiority of the optimization algorithm, the method of the invention is simulated and verified by adopting an example, and the obtained technical effects comprise:
establishing an optimal airspace model for planning an optimal airspace of the electronic jammer by fully considering the side key points of a decision maker;
by using an improved optimization algorithm, the optimal airspace reference point is solved, so that the optimal airspace required by a decision maker can be quickly obtained, and the planned airspace is scientific and effective.
Description of the drawings:
FIG. 1 is a schematic diagram of the operation of an jammer;
FIG. 2 is a distribution diagram of an enemy radar net;
FIG. 3 is a flow chart of a method of the present invention;
FIG. 4 is a schematic diagram of a detection range of a radar without interference;
FIG. 5 is a comparison of GWO and PSO;
FIG. 6 is a situation diagram after simulation 1 interference;
fig. 7 is a diagram of the situation after the interference of simulation 2.
Detailed Description
The following describes embodiments of the present invention:
radar detection range under electronic interference
The distance support interference (SOJ) means that a special electronic interference plane is dispatched to reach a preset airspace in advance to fly in a runway shape, if the interference antenna is arranged on two sides of the plane, the interference antenna flies in a transverse runway shape, and if the interference antenna is arranged on the front side and the rear side, the interference antenna flies in a longitudinal runway shape. Under the cooperative command of the early warning machine, an interference signal is actively released to form a certain interference suppression area for threatening radar by an enemy, so that the safety and the penetration of a warplane are realized.
The target fluctuation is not considered, the multipath influence is ignored, the transmitting signal and the receiving signal share the same antenna, and the radar detection range after the suppression of the single jammer is as follows:
wherein, KjTo suppress the coefficient, PtFor transmitting signal power to radar, GtFor the power gain of the radar transmitting antenna, sigma is the cross-sectional area of the radar target, RjDistance of radar to jammer, PjFor jammer power, GjFor jammer antenna gain, gammajFor the polarization loss of the antenna, G (θ) is the radar antenna gain at θ degrees from the maximum direction of the main lobe, and according to the empirical formula G (θ) is:
θ0.5is the main lobe width, and k is a constant, generally 0.04 to 0.1. Because the power has the superposition property, the radar detection range after the suppression of a plurality of jammers is as follows:
since in reality the number of radars is always larger than the number of jammers, the invention selects a "one-to-one" interference pattern.
Safety interval for route
In the actual flight process, due to the influence of the deviation of the path positioning of the penetration fighter aircraft, technical errors of pilots, wind speed and the like, the aircraft often deviates from the reference penetration path, so the shortest distance between the detection range of the radar after interference and the penetration route, namely the safety interval of the route, needs to be considered, as shown in fig. 1, and the reference signs in fig. 1 include a penetration starting point 1, a penetration ending point 2, an interference applying moment 3, an interference ending moment 4, a route safety interval 5, a post-interference detection range 6 and a pre-interference detection range 7. The safe course interval is the key to the fighter whether to be safe and break out, and the safe course interval formed by the interference of the electronic jammer is not less than the minimum required course interval of the break out fighter.
Effective interference time
Since the jammer is responsible for the tasks of shielding and supporting the fighter, the attempt of preventing the fighter by the party can be exposed by applying the jammer too early, so that the enemy can prepare for the jammer early, the safety of the jammer can be threatened by ending the jammer too late, and the completion of the tasks cannot be guaranteed by applying the jammer too late or ending the jammer too early. Therefore, the timing of the jammer releasing the jammer and ending the jammer, i.e., the effective jamming time, is also critical. Meanwhile, the antennas of the jammers are arranged in front of and behind the airplane, the actual jamming time is the straight line part of the runway-type airspace, and the radar is not interfered at the turning position, so that the effective jamming time is an important basis for planning the size of the airspace.
In modern war, electronic space has become the fifth space for both enemy and me to compete. In order to effectively enhance the four-antibody capability, enemies often adopt the radar networking technology to carry out full-area detection on the target area of the enemy. To achieve successful penetration, penetration fighters are often coordinated with a number of jammers. When a plurality of jammers are dispatched, if the jammers are only planned in an airspace according to the experience of a commander, the jammers are difficult to reach a preset interference effect, and meanwhile, due to the fact that the planning is not fine, airspace resources are wasted, and the completion of other battle tasks can be hindered.
Under the situation of both enemies and the self, the cooperative opportunity of the jammer and the aggressor is considered, the reference point of an airspace is searched in the command control area of the early warning machine of the self according to the radar distribution situation of the enemy and the performance of the jammer, and the size of the airspace is reasonably divided by combining the relevant parameters of the jammer, so that the performance and the safety of the jammer are comprehensively considered according to time cooperation, and a route safety interval is formed for a specific defense burst route, so that the warplane can safely pass through a threat zone according to a preset defense burst route.
Model building
Based on the above problems, considering that the distribution of the enemy radar net is shown in fig. 2, the fig. 2 includes a radar 11, a radar 12 and a radar 13, and the penetration fighter plane wants to perform penetration according to a preset route, and the probability of being detected and destroyed is extremely high. Therefore, the jammers are reasonably arranged and a flight airspace is planned for the jammers within the command control range of the early warning machine of one party, and on the premise that the positions of the jammers are always out of the detection range of each radar, the safe interval of the flight path of the anti-penetration fighter relative to each threat radar is larger than the required minimum safe interval of the flight path, and the larger the interval of the flight path is, the higher the probability of successful anti-penetration of the fighter of one party is. The key of the airspace division is the selection of the airspace reference point, the position of the interference releasing moment of the interference machine is selected as the reference point of the airspace, and as long as the interference machine can meet the requirement at the position, any position in the effective interference time can meet the requirement. According to the theory, the spatial reference point model of the interference machine is established as follows:
the constraint conditions that the model should satisfy are:
(1) self-safety constraint of the jammer: that is, the space domain where the jammer is located must be out of the detection range of each radar
(2) Commanding and controlling area constraint: that is, the airspace of the jammer must be within the command and control area of the early warning machine of the same party
xj∈[xmin,xmax],yj∈[ymin,ymax]
(3) Safety constraint of the defense fighter: i.e. the flight path safety interval formed after the disturbance must meet the minimum flight path safety interval d required for fighting aircrafti≥dmin
Wherein d isiThe safety interval between the outburst prevention air route and the ith threat radar air route is suppressed; lambda [ alpha ]1Weight, λ, representing the safe interval of the flight path2Weight of interference machine and central point of radar network, and lambda1+λ2＝1；xj0,yj0Is the abscissa, x, of the spatial reference point of the jth jammerj,yjThe horizontal and vertical coordinates of the airspace of the jth interference machine are shown; x is the number ofi,yiIs the central abscissa, [ x ] of the ith radarmin,xmax],[ymin,ymax]The command control range of the early warning machine is set for one party; x is the number of0,y0Is the horizontal and vertical coordinate of the center of the radar net,
after the position of the spatial reference point is determined, the actual size of the spatial domain of the jammer is calculated according to the following three formulas.
R＝v2/(g×tanγ) (5)
L＝v·t+2R (6)
D＝2R (7)
Wherein R is turning radius, v is the speed of the jammer, g is the acceleration of gravity, gamma is the turning slope, L is the airspace length, t is the effective jamming time, and D is the airspace width.
Improved optimization algorithm
The Optimization algorithm (GHO) was proposed by Mirjalili et al in 2014[14]The algorithm simulates a leader hierarchy and a hunting mechanism. The algorithm has the advantages of simple principle, high operation speed, less adjustment parameters and good convergence, is widely applied to various fields, and is easy to fall into local optimization. Therefore, the invention improves the global search performance by adopting the nonlinear adjustment parameter, and introduces the condition that the optimization speed is slowed down because of adopting the nonlinear adjustment parameter for the memory function balance.
Basic GWO algorithm
The divided social classes are simulated in the optimization algorithm according to the goodness of the solution problem, the best solution is regarded as α wolf, the second best solution and the third best solution are named as β wolf and delta wolf respectively, other candidate solutions are assumed to be omega wolf, under the leading of α wolf, the hunting objects are searched and gradually approached, after the specific position of the hunting objects is determined, a surrounding ring is formed and the range is gradually reduced, and finally the attack is implemented.
In the hunting process, the wolf pack updates the position according to the following formula,
where t represents the current number of iterations,andis a vector of co-ordinated coefficients,is the position vector of the prey,the position vector of the representation is,in order to adjust the parameters of the device,andis random [0,1 ]]The vector of (1).
Since the location of the prey is unknown (i.e., the optimal solution) during the algorithm's operation, α, β, δ are considered to be closer to the prey location according to the social ranking, so the population can be updated according to the α, β, δ locations:
improved strategy
In the above description, it can be seen that the tuning parametersIs crucial to the operation of the whole algorithm. When in useWhen the search time is larger, the algorithm search step is large, and the global search capability is strong; when in useWhen the algorithm is small, the convergence of the algorithm is good. Due to the fact thatLinearly decreasing from 2 to 0 during the iteration, this control may be trapped in a local optimum[18]Therefore, it is necessary to introduce a nonlinear tuning parameter.
Meanwhile, considering that the introduction of nonlinear adjustment parameters can reduce the optimizing speed, the memory function in the particle swarm algorithm is adopted to enhance the optimizing speed, so that the following steps are provided:
is [0,1 ]]Random number of (1), c1To adjust the coefficients.Is the historically passed best location point.
GWO Algorithm Steps improvement
According to the spatial reference points sought by the present invention, the steps for improving GWO algorithm are as follows:
step 1: determining the number of initial airspace reference points, the maximum iteration number, the dimension, an upper bound and a lower bound, adjusting parameters and initializing the parameters, wherein t is 1;
step 2: randomly selecting initial airspace reference points, and calculating the safe course interval of each airspace reference point;
step 3, judging whether the population meets three constraints in section 2.2, if not, making the fitness negative infinity, returning to the step 2, otherwise, calculating the fitness value of each population according to the formula (4), and recording the optimal fitness value of the first three in the fitness arrangement and the corresponding airspace reference point (α, delta);
step 4, let t become t +1
Step 5, updating according to the formulas (16), (9) and (10)
Step 6, updating α the position of delta according to the formulas (12) to (14);
and 7: updating the position of the spatial reference point according to equation (17);
and 8: judging whether the maximum iteration times is reached, if so, finishing the algorithm and outputting an optimal result, otherwise, returning to the step 4;
the specific flow chart is shown in fig. 3.
Simulation instance analysis
Suppose the coordinates of threats 1, 2, 3 are (120 ), (200,50), (115,0), respectively; threat parameters of radar and parameters of jammers are derived from document 19: pt＝4500kW,Gt＝40dB,θ0.5＝4°，Pj＝200kW,Gj＝20dB,rj＝0.5,Kj0.5, 500km/h, 20 ° for V. The flying speed of the penetration fighter is 900 km/h. In order to reduce the calculation amount, radar parameters of all parts of the enemy are considered to be consistent with the model of the jammer used by the enemy.
Initial situation analysis: fig. 4 is a detection range of undisturbed radars, wherein a blue line segment is a route preset by the civil defense fighter, a green dot is a position threatening the radars, a red circle is a detection range of the radars, and a command control area of the civil defense fighter is 250 × 250km, namely a magenta containing area. If no interference measures are taken, the probability that a penetration fighter is detected and destroyed is very high.
According to the theory and the battlefield situation, in order to obtain the safety width of the defense route of at least 10km, two interference machines are adopted by the party to carry out one-to-one interference on the defense route. And finding the optimal spatial reference point by using an improved GWO algorithm.
Simulation 1: the improved GWO algorithm initial parameter settings are as follows: dim is 4, the number of initial population searchAgents _ no is 50, the maximum number of iterations Max _ iter is 100, λ1＝0.9，λ20.1, and-100 and 150, respectively. And is in contrast to the basic GWO algorithm and Particle Swarm Optimization (PSO). The comparative plot of fig. 5, as well as the schematic of fig. 6 and the data of table 1 were obtained by programming the simulation in Matlab language.
As can be seen from fig. 5, the improved optimization algorithm (IGWO) has better optimization effect than the original optimization algorithm, and is not easy to fall into local optimization. Meanwhile, the convergence rate is high. IGWO is superior to Particle Swarm Optimization (PSO) in both optimizing effect and convergence rate. The superiority of the improved optimization algorithm is fully reflected.
TABLE 1
As can be seen from the simulation of fig. 6, fig. 6 includes a jammer 14 and a jammer 15, so that for a specific combat purpose, the penetration fighter can fly according to a predetermined flight path, and the jammers of our party should fly according to the reference points and airspace parameters given in table 1. According to a given scheme, the safe space of the air route between the penetration fighter and each radar can be ensured to meet the minimum required safe space of the air route, and the size of the marked airspace is much smaller than the range of the traditional electronic airspace (100-150) × (80-100) km. The interference effect is guaranteed, meanwhile, the airspace range is greatly reduced, and the purpose of efficiently and flexibly using airspace resources is achieved.
Simulation 2: lambda [ alpha ]1＝0.2，λ2With the remaining parameters unchanged, the simulation was programmed in Matlab language to obtain the data of fig. 7 and table 2.
TABLE 2
As can be seen from the simulation of FIG. 7, by increasing the coefficient λ2On the premise of ensuring the minimum safety interval required by the penetration fighter, the distance between the jammer and the center of the radar net is properly adjusted, so that the safety of the jammer can be fully ensured. This also represents a greater emphasis on interfering equipment protection by the commander.
The foregoing is a preferred embodiment of the present invention, and it should be noted that it is obvious to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and these modifications and improvements should be considered as the protection scope of the present invention.
Claims (2)
1. An improved optimization algorithm-based electronic jammer airspace planning method is characterized by specifically comprising the following steps:
step 1: determining the number of initial airspace reference points, the maximum iteration number, the dimension, an upper bound and a lower bound according to an airspace reference point model of an interference machine, adjusting parameters and initializing the parameters, wherein t is 1;
step 2: randomly selecting initial airspace reference points, and calculating the safe course interval of each airspace reference point;
and step 3: whether the population meets three constraints is judged,
constraint 1: self-safety constraint of the jammer: that is, the airspace where the jammer is located must be outside the detection range of each radar;
constraint 2: commanding and controlling area constraint: namely, the airspace of the jammer must be within the command control area of the early warning machine of one party;
constraint 3: safety constraint of the defense fighter: that is, the safety interval of the flight path formed after the interference must meet the minimum safety interval of the flight path required by the fighter plane;
if not, the fitness is made negative infinity, the step 2 is returned, otherwise, the fitness value of each population is calculated according to a formula I, and the optimal fitness value of the third group before the fitness arrangement and the corresponding airspace reference point thereof are recorded, namely α and delta;
wherein d isiThe safety interval between the outburst prevention air route and the ith threat radar air route is suppressed; lambda [ alpha ]1Weight, λ, representing the safe interval of the flight path2Weight of interference machine and central point of radar network, and lambda1+λ2＝1；xj0,yj0The horizontal and vertical coordinates of the spatial reference point of the jth interference machine;
step 4, making t equal to t + 1;
step 5, updating according to a formula two, a formula three and a formula four respectively
Where t represents the current number of iterations,andis a vector of co-ordinated coefficients,in order to adjust the parameters of the device,andis random [0,1 ]]The vector of (1);
step 6, updating α positions and delta positions respectively according to a formula five, a formula six and a formula seven;
and 7: according to the formula eight, updating the position of the airspace reference point;
wherein,is [0,1 ]]Random number of (1), c1To adjust the coefficient。Is the best position point historically passed;
and 8: and (4) judging whether the maximum iteration times is reached, if so, finishing the algorithm and outputting an optimal result, otherwise, returning to the step (4).
2. The method for the spatial domain planning of the jammer based on the improved optimization algorithm of claim 1, wherein in the method, constraint 1, constraint 2 and constraint 3 in step 3 are respectively judged according to formula ten, formula eleven and formula twelve;
xj∈[xmin,xmax],yj∈[ymin,ymax]formula eleven
di≥dminFormula twelve
Wherein x isj,yjThe horizontal and vertical coordinates of the airspace of the jth interference machine are shown; x is the number ofi,yiIs the central abscissa, [ x ] of the ith radarmin,xmax],[ymin,ymax]The command control range of the early warning machine is set for one party; x is the number of0,y0Is the horizontal and vertical coordinate of the center of the radar net,
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110765586A (en) * | 2019-09-30 | 2020-02-07 | 中国人民解放军空军预警学院 | Radar networking optimization station distribution method based on improved particle swarm optimization |
| CN111427017A (en) * | 2020-04-22 | 2020-07-17 | 北京航天长征飞行器研究所 | Interference resource allocation method and device |
| CN114444398A (en) * | 2022-02-08 | 2022-05-06 | 扬州宇安电子科技有限公司 | Grey wolf algorithm-based networking radar cooperative interference resource allocation method |
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