CN106197426A - A kind of unmanned plane emergency communication paths planning method and system - Google Patents

A kind of unmanned plane emergency communication paths planning method and system Download PDF

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CN106197426A
CN106197426A CN201610505717.0A CN201610505717A CN106197426A CN 106197426 A CN106197426 A CN 106197426A CN 201610505717 A CN201610505717 A CN 201610505717A CN 106197426 A CN106197426 A CN 106197426A
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李天松
黄艳虎
卢亚军
周海燕
邱云翔
李思民
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Guilin University of Electronic Technology
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Abstract

本发明涉及一种无人机应急通信路径规划方法及系统,其方法包括以下步骤:步骤1.对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,标注无人机的起始点和目标点,以及标注雷达分布和地形信息;步骤2.根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时构建飞行限定模型;步骤3.根据飞行威胁模型和飞行限定模型构建飞行路线;步骤4.通过混沌遗传算法对飞行路线进行优化,确定最终飞行路线。相对现有技术,本发明能安全避开低空障碍物和雷达的干扰,到达指定终点飞行时间最短和路径最优,具有较好的实时性和快速性。

The present invention relates to a UAV emergency communication path planning method and system. The method includes the following steps: Step 1. Carry out three-dimensional grid division for the flying space of the UAV, obtain grid nodes, construct a grid diagram, and mark no The starting point and target point of the man-machine, as well as marking the radar distribution and terrain information; step 2. Construct a flight threat model according to the radar distribution and terrain information in the UAV flight space, and build a flight limit model at the same time; step 3. According to the flight threat The flight path is constructed by the model and the flight-limited model; Step 4. Optimizing the flight path through a chaotic genetic algorithm to determine the final flight path. Compared with the prior art, the present invention can safely avoid low-altitude obstacles and radar interference, has the shortest flight time and optimal path to reach the designated destination, and has better real-time and rapidity.

Description

一种无人机应急通信路径规划方法及系统A UAV emergency communication path planning method and system

技术领域technical field

本发明涉及无人机技术领域,特别涉及一种无人机应急通信路径规划方法及系统。The invention relates to the technical field of unmanned aerial vehicles, in particular to a method and system for planning emergency communication paths of unmanned aerial vehicles.

背景技术Background technique

无人机在应急通信、国土安防、空中协警、紧急救援和农业种植领域得到了越来越广泛的应用,无人机更因其独特的垂直起降、空中悬停性能而倍受青睐.在复杂、受限的空间中,无人机可以利用其悬停、横飞、倒飞等飞行方式穿梭于障碍物之间,完成通信基站搭建、地形测量、场景拍摄、抢险救灾等任务。与二维平面上的车辆和移动机器人不同的是,任何碰撞对于无人直升机都是致命的,直接导致预定任务失败,自主快速避险、寻找最优航迹能力是其完成任务的关键所在。因此在确保安全飞行的前提下快速实时的规划出最优路径已经成为无人机行业目前亟待解决的问题。UAVs are more and more widely used in emergency communications, homeland security, air police, emergency rescue and agricultural planting. UAVs are more popular because of their unique vertical take-off and landing and air hovering performance. In a complex and restricted space, UAVs can use its hovering, horizontal flying, inverted flying and other flying methods to shuttle between obstacles and complete tasks such as communication base station construction, terrain survey, scene shooting, emergency rescue and disaster relief. Different from vehicles and mobile robots on a two-dimensional plane, any collision is fatal to an unmanned helicopter, which directly leads to the failure of the scheduled mission. The ability to autonomously and quickly avoid danger and find the optimal trajectory is the key to its mission completion. Therefore, fast and real-time planning of the optimal path under the premise of ensuring safe flight has become an urgent problem to be solved in the UAV industry.

目前,常用的无人机航路规划算法有线性、非线性规划方法、A*算法、蚁群算法等。At present, the commonly used UAV route planning algorithms include linear and nonlinear planning methods, A* algorithm, ant colony algorithm, etc.

线性、非线性无人机路径规划方法,可以综合全方面考虑无人机飞行过程中与路径相关的安全性、可执行性等,缺点是这些方法要求解一系列的约束优化问题,计算量大、计算时间长、收敛速度慢且易受局部最小值影响陷入局部最优解,适用于局部航迹规划。Linear and non-linear UAV path planning methods can comprehensively consider the safety and executability related to the path during UAV flight. The disadvantage is that these methods need to solve a series of constrained optimization problems, and the amount of calculation is large. , long calculation time, slow convergence speed and easy to be affected by local minimum and fall into local optimal solution, which is suitable for local track planning.

A*算法由于其速度快的特点,得到了广泛的应用,其性能依赖启发函数的选取,而实际中得到最优的启发函数是有一定难度的的,因此A*算法一般只能搜索到一个相对较优的路径,当无人机飞行航迹发生改变时不能利用在首次搜索中得到的信息,只能重新进行搜索,这就需要比较长的时间重新规划路径。The A* algorithm has been widely used due to its fast speed. Its performance depends on the selection of the heuristic function, but it is difficult to obtain the optimal heuristic function in practice. Therefore, the A* algorithm generally can only search for one For a relatively optimal path, when the flight path of the UAV changes, the information obtained in the first search cannot be used, and the search can only be performed again, which requires a relatively long time to re-plan the path.

蚁群算法是蚂蚁在觅食时随机选择一个方向搜索,当一只蚂蚁发现食物源后,以某种方式告诉同伴一起搬运食物,当多只蚂蚁合作搬运之后所走的路径就变成了最短的路径。蚁群算法是一种全局规划方法,可同时考虑多个目标,但当环境出现突发变化或需实时规划时,蚁群算法不能保证在有限时间内很快的搜索到路径。The ant colony algorithm is that ants randomly choose a direction to search when they are looking for food. When an ant finds a food source, it tells its companions to carry the food together in a certain way. When multiple ants cooperate to carry the food, the path they take becomes the shortest. path of. Ant colony algorithm is a global planning method that can consider multiple goals at the same time, but when the environment changes suddenly or real-time planning is required, the ant colony algorithm cannot guarantee that the path can be searched quickly within a limited time.

发明内容Contents of the invention

本发明所要解决的技术问题是提供一种无人机应急通信路径规划方法及系统,能安全避开低空障碍物和雷达的干扰,到达指定终点飞行时间最短和路径最优,同时在原有遗传算法基础上,利用混沌序列来控制遗传操作中的交叉和变异,避免了完全随机操作的盲目性,具有较好的实时性和快速性,得到的飞行路线更逼近实际的无人机最优航迹。The technical problem to be solved by the present invention is to provide a UAV emergency communication path planning method and system, which can safely avoid the interference of low-altitude obstacles and radar, and reach the designated destination with the shortest flight time and optimal path. On the basis of this, the use of chaotic sequences to control the crossover and mutation in genetic operations avoids the blindness of completely random operations, and has better real-time and rapidity, and the obtained flight path is closer to the actual UAV optimal trajectory .

本发明解决上述技术问题的技术方案如下:一种无人机应急通信路径规划方法,包括以下步骤:The technical solution of the present invention to solve the above-mentioned technical problems is as follows: a UAV emergency communication path planning method, comprising the following steps:

步骤1.对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,在所述网格图上标注无人机的起始点和目标点,以及标注无人机飞行空间内的雷达分布和地形信息;Step 1. Carry out three-dimensional grid division on the flying space of the UAV, obtain grid nodes, construct a grid diagram, mark the starting point and target point of the UAV on the grid diagram, and mark the flight of the UAV Radar distribution and terrain information in space;

步骤2.根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时根据无人机的飞行技术参数构建飞行限定模型;Step 2. Construct a flight threat model according to the radar distribution and terrain information in the flight space of the UAV, and construct a flight limitation model according to the flight technical parameters of the UAV;

步骤3.根据飞行威胁模型和飞行限定模型在无人机的起始点和目标点之间构建飞行路线;Step 3. Construct a flight route between the starting point and the target point of the drone according to the flight threat model and the flight limitation model;

步骤4.通过混沌遗传算法对飞行路线进行优化,确定最终飞行路线。Step 4. Optimizing the flight route through the chaotic genetic algorithm to determine the final flight route.

本发明的有益效果是:能安全避开低空障碍物和雷达的干扰,到达指定终点飞行时间最短和路径最优,同时在原有遗传算法基础上,利用混沌序列来控制遗传操作中的交叉和变异,取代原有完全随机的交叉和变异操作,精确确定是否进行交叉或变异操作以及确定交叉或变异操作的具体位置等两个方面,避免了随机操作的盲目性,使求得的解精度高,收敛速度快,同时本技术方案具有较好的实时性和快速性,使无人机在执行应急通信、空中救援等任务时,搜索到的航迹更逼近实际的无人机最优航迹。The beneficial effect of the present invention is: it can safely avoid the interference of low-altitude obstacles and radar, the flight time to reach the designated destination is the shortest and the path is optimal, and at the same time, on the basis of the original genetic algorithm, the chaotic sequence is used to control the crossover and variation in the genetic operation , to replace the original completely random crossover and mutation operations, to accurately determine whether to perform crossover or mutation operations and to determine the specific position of the crossover or mutation operations, avoiding the blindness of random operations, and making the obtained solutions highly accurate. The convergence speed is fast, and at the same time, the technical solution has better real-time and rapidity, so that when the UAV performs tasks such as emergency communication and air rescue, the searched track is closer to the actual optimal track of the UAV.

在上述技术方案的基础上,本发明还可以做如下改进。On the basis of the above technical solutions, the present invention can also be improved as follows.

进一步,所述飞行威胁模型具体为:Further, the flight threat model is specifically:

min W=k1Jthreat+k2Jfuelmin W=k 1 J threat +k 2 J fuel ;

其中Jthreat为雷达威胁代价,k1(k1∈(0,1))为雷达威胁代价的权重,Jfuel为燃油代价,k2(k2∈(0,1))为燃油代价的权重。Where J threat is radar threat cost, k 1 (k 1 ∈ (0, 1)) is the weight of radar threat cost, J fuel is fuel cost, k 2 (k 2 ∈ (0, 1)) is the weight of fuel cost .

采用上述进一步方案的有益效果是:通过雷达威胁和燃油威胁的限定建模,保证无人机无威胁飞行,选择无人机飞行路径更加精准。The beneficial effect of adopting the above-mentioned further solution is: through the limited modeling of radar threat and fuel threat, it is ensured that the drone flies without threat, and the flight path of the drone is selected more accurately.

进一步,所述飞行限定模型包括:Further, the flight-limited model includes:

无人机在遇到障碍物时改变姿态直飞的距离r小于无人机的起始点至障碍点之间的距离Smin,r<SminWhen the UAV encounters an obstacle, the distance r from which the UAV changes its attitude and flies straight is less than the distance S min between the starting point of the UAV and the obstacle point, and r<S min .

采用上述进一步方案的有益效果是:通过对无人机在改变姿态时直飞的距离限定,能保证无人机按设定路线安全飞行。The beneficial effect of adopting the above-mentioned further solution is that by limiting the direct flight distance of the UAV when changing its attitude, it can ensure that the UAV can fly safely according to the set route.

进一步,所述飞行限定模型包括:Further, the flight-limited model includes:

无人机在探测到障碍物时悬停的时间Tmin小于无人机飞行的总时长t,Tmin<t。The hovering time T min of the UAV when an obstacle is detected is less than the total flight time t of the UAV, and T min < t.

采用上述进一步方案的有益效果是:通过无人机在探测到障碍物时悬停时间的限定,能保证无人机按设定路线顺畅飞行。The beneficial effect of adopting the above further solution is that the drone can be guaranteed to fly smoothly according to the set route by limiting the hovering time when the drone detects an obstacle.

进一步,所述飞行限定模型包括:Further, the flight-limited model includes:

飞行路线的高度H大于无人机飞行设定的最低飞行高度Hmin,且小于无人机飞行设定的最高飞行高度Hmax,Hmin<H<HmaxThe altitude H of the flight route is greater than the minimum flight altitude H min set for the drone flight, and smaller than the maximum flight altitude H max set for the drone flight, and H min <H<H max .

采用上述进一步方案的有益效果是:通过飞行路线的高度H的限定,能保证无人机按飞行路线顺畅飞行。The beneficial effect of adopting the above-mentioned further solution is that the unmanned aerial vehicle can be guaranteed to fly smoothly according to the flight route through the limitation of the height H of the flight route.

进一步,所述飞行限定模型包括:Further, the flight-limited model includes:

飞行路线的距离L小于无人机飞行极限距离的二分之一,L<Lmax/2。The distance L of the flight route is less than half of the flight limit distance of the UAV, and L<L max /2.

优选的,所述飞行限定模型包括:无人机沿着x坐标轴的正方向飞行,当前所在节点的坐标为(x1,y1,z1),下一节点的坐标为(x2,y2,z2),无人机在水平方向和垂直方向偏转的最大角度Ф满足:Preferably, the flight limitation model includes: the UAV flies along the positive direction of the x coordinate axis, the coordinates of the current node are (x1, y1, z1), and the coordinates of the next node are (x2, y2, z2) , the maximum deflection angle Ф of the UAV in the horizontal direction and vertical direction satisfies:

|| arctanarctan (( ythe y 22 -- ythe y 11 xx 22 -- xx 11 )) || &le;&le; &phi;&phi; mm aa xx || arctanarctan (( zz 22 -- zz 11 xx 22 -- xx 11 )) || &le;&le; &gamma;&gamma; mm aa xx ;;

其中Фmax为无人机水平方向偏转的极限角度;уmax为无人机垂直方向偏转的极限角度。Among them, Ф max is the limit angle of UAV horizontal deflection; у max is the limit angle of UAV vertical deflection.

采用上述进一步方案的有益效果是:通过飞行路线的高度H的限定,能保证无人机按飞行路线顺畅飞行。The beneficial effect of adopting the above-mentioned further solution is that the unmanned aerial vehicle can be guaranteed to fly smoothly according to the flight route through the limitation of the height H of the flight route.

进一步,通过混沌遗传算法对飞行路线进行优化具体包括以下步骤:Further, optimizing the flight route through the chaotic genetic algorithm specifically includes the following steps:

步骤4.1.利用混沌运动Logistic映射方程xk+1=uxk(1-xk)(1),随机生成初始混沌序列,其中u是控制参数,当u=4时,上式完全处于混沌状态,且在[0,1]内是遍历的;Step 4.1. Use the chaotic motion Logistic mapping equation x k+1 =ux k (1-x k )(1) to randomly generate the initial chaotic sequence, where u is the control parameter. When u=4, the above formula is completely in a chaotic state , and it is traversed within [0,1];

步骤4.2.将一次产生的混沌变量XK按(2)式映射成新的混沌变量X,同时将整个遍历区间[0,1]映射到优化变量的取值区间[a,b];Step 4.2. Map the chaotic variable X K generated once into a new chaotic variable X according to formula (2), and map the entire traversal interval [0,1] to the value interval [a,b] of the optimized variable at the same time;

Xx == aa ++ xx ii kk (( bb -- aa )) -- -- -- (( 22 )) ;;

步骤4.3.利用所述混沌变量,进行混沌搜索;Step 4.3. Use the chaotic variable to perform chaotic search;

通过混沌发生器产生的随机步长在无人机执行任务的区间范围[a,b]内对飞行路线进行扰动,同时飞行路线实时根据目标点和初始点连线的偏离程度Li以及无人机距离威胁的最近距离Ci,计算飞行路线中路段个体的适值f(X),得到路段个体的适值由高到低进行排序,对适值低的10%路段个体进行淘汰,剩下适值高的90%路段个体;The random step size generated by the chaos generator disturbs the flight route within the range [a,b] of the drone’s mission, and the flight route is based on the deviation degree L i of the target point and the initial point in real time and the unmanned Calculate the fitness value f(X) of the road section individuals in the flight route, and sort the fitness values of the road section individuals from high to low, and eliminate 10% of the road section individuals with low fitness values, leaving the high fitness values 90% of individual road sections;

步骤4.4.循环步骤4.1至步骤4.3直到路段个体数量达到设定规模,组合成初始种群;Step 4.4. Repeat steps 4.1 to 4.3 until the number of individuals in the road section reaches the set scale, and combine them into an initial population;

步骤4.5.在初始种群中适值高的90%个体中随机选择两个配对个体,按混沌交叉规律进行交叉操作;Step 4.5. Randomly select two paired individuals among the 90% individuals with high fitness in the initial population, and perform the crossover operation according to the chaotic crossover rule;

步骤4.6.将配对个体按混沌变异规律进行变异操作,得多个变异个体,将多个变异个体与初始种群中适值排序中前10%的个体进行合并构成二代种群;Step 4.6. The paired individuals are mutated according to the law of chaotic variation to obtain multiple mutated individuals, and the multiple mutated individuals are combined with the top 10% individuals in the initial population to form the second generation population;

步骤4.7.对二代群体中两个相同个体中的一个进行删除,同时对二代种群中适值排序中后10%的个体进行淘汰,得二代种群中适值高的90%个体;Step 4.7. Delete one of the two identical individuals in the second-generation population, and eliminate the bottom 10% individuals in the second-generation population in the fitness ranking, and obtain 90% of individuals with higher fitness in the second-generation population;

步骤4.8.对二代种群中适值高的90%个体进行混沌遗传操作,生成多个遗传个体,并构成遗传种群,将遗传种群中适值低的90%个体进行淘汰,得遗传种群中适值高的10%个体;Step 4.8. Perform chaotic genetic operations on 90% of the individuals with high fitness in the second generation population, generate multiple genetic individuals, and form a genetic population, eliminate 90% of the individuals with low fitness in the genetic population, and obtain the genetic population with high fitness 10% individual;

步骤4.9.将遗传种群中适值高的10%个体进行解码,规划得出最终的无人机飞行路径。Step 4.9. Decode the 10% individuals with high fitness in the genetic population, and plan to obtain the final UAV flight path.

采用上述进一步方案的有益效果是:在遗传算法中加入混沌操作,利用混沌序列来控制遗传操作中的交叉和变异,以取代原有的在一定概率下完全随机的交叉和变异操作,避免完全随机操作的盲目性;有效的防止和克服进化中因群体多样性减少而导致筛选不精准。The beneficial effect of adopting the above further scheme is: add chaotic operation to the genetic algorithm, use chaotic sequence to control the crossover and mutation in the genetic operation, to replace the original crossover and mutation operation that is completely random under a certain probability, and avoid complete randomness. The blindness of operation; effectively prevent and overcome the inaccurate screening caused by the reduction of population diversity in evolution.

进一步,适值计算具体为:Further, the fitness value calculation is specifically as follows:

ff (( Xx )) == &Sigma;&Sigma; ii == 11 NN -- 11 LL ii (( NN -- ii )) ** dd 00 ** 1010 dd ii ,, minmin ** ll ii (( Xx ii )) ** CC ii ;;

其中是路径偏离目标点与初始点连线的偏离程度惩罚系数;in is the penalty coefficient for the degree of deviation of the path from the line connecting the target point and the initial point;

Li是第i路径点到目标点的距离,d0为航路段的长度,通常根据无人机的导航方式确定,Li is the distance from the i-th path point to the target point, and d0 is the length of the route segment, which is usually determined according to the navigation method of the UAV.

(N-i)*d0是沿着初始点与目标连线方向的距离,li是路径段的实际距离;其中是安全性的惩罚系数;(Ni)*d0 is the distance along the direction of the initial point and the target line, l i is the actual distance of the path segment; where is the security penalty coefficient;

di,min是第i路径段路径距离威胁的最近距离,Ci为路径的目标点与其前一点之间的偏转角满足约束的惩罚系数。di, min is the shortest distance between the i-th path segment and the threat, and C i is the penalty coefficient that the deflection angle between the target point of the path and its previous point satisfies the constraint.

采用上述进一步方案的有益效果是:提升适值计算的精准度,保证路线选择最优。The beneficial effect of adopting the above-mentioned further solution is: to improve the accuracy of the fitness value calculation and ensure the optimal route selection.

本发明解决上述技术问题的另一技术方案如下:一种无人机应急通信路径规划系统,包括:Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a UAV emergency communication path planning system, comprising:

划分模块,用于对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,在所述网格图上标注无人机的起始点和目标点,以及标注无人机飞行空间内的雷达分布和地形信息;The division module is used for performing three-dimensional grid division on the flying space of the UAV, obtaining grid nodes, constructing a grid diagram, marking the starting point and target point of the UAV on the grid diagram, and marking no one Radar distribution and terrain information in the flight space of the aircraft;

建模模块,用于根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时根据无人机的飞行技术参数构建飞行限定模型;The modeling module is used to construct a flight threat model according to the radar distribution and terrain information in the flight space of the UAV, and to construct a flight limitation model according to the flight technical parameters of the UAV;

构建路线模块,用于根据飞行威胁模型和飞行限定模型在无人机的起始点和目标点之间构建飞行路线;Constructing a route module for constructing a flight route between the starting point and the target point of the drone according to the flight threat model and the flight restriction model;

筛选模块,用于通过混沌遗传算法对飞行路线进行优化,确定最终飞行路线。The screening module is used to optimize the flight route through the chaotic genetic algorithm to determine the final flight route.

本发明的有益效果是:能安全避开低空障碍物和雷达的干扰,到达指定终点飞行时间最短和路径最优,同时在原有遗传算法基础上,利用混沌序列来控制遗传操作中的交叉和变异,取代原有完全随机的交叉和变异操作,精确确定是否进行交叉或变异操作以及确定交叉或变异操作的具体位置等两个方面,避免了完全随机操作的盲目性,使求得的解精度高,收敛速度快,同时本技术方案具有较好的实时性和快速性,使无人机在执行应急通信、空中救援等任务时,搜索到的航迹更逼近实际的无人机最优航迹。The beneficial effect of the present invention is: it can safely avoid the interference of low-altitude obstacles and radar, the flight time to reach the designated destination is the shortest and the path is optimal, and at the same time, on the basis of the original genetic algorithm, the chaotic sequence is used to control the crossover and variation in the genetic operation , to replace the original completely random crossover and mutation operations, to accurately determine whether to perform crossover or mutation operations and to determine the specific position of the crossover or mutation operations, avoiding the blindness of completely random operations, and making the solution obtained with high accuracy , the convergence speed is fast, and at the same time, this technical solution has better real-time and rapidity, so that when the UAV performs tasks such as emergency communication and air rescue, the searched track is closer to the actual optimal track of the UAV .

附图说明Description of drawings

图1为本发明一种无人机应急通信路径规划方法的流程图;Fig. 1 is the flow chart of a kind of unmanned aerial vehicle emergency communication path planning method of the present invention;

图2为本发明一种无人机应急通信路径规划系统的模块框图。Fig. 2 is a module block diagram of a UAV emergency communication path planning system according to the present invention.

附图中,各标号所代表的部件列表如下:In the accompanying drawings, the list of parts represented by each label is as follows:

1、划分模块,2、建模模块,3、构建路线模块,4、筛选模块。1. Division module, 2. Modeling module, 3. Route building module, 4. Screening module.

具体实施方式detailed description

以下结合附图对本发明的原理和特征进行描述,所举实例只用于解释本发明,并非用于限定本发明的范围。The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

如图1所示,一种无人机应急通信路径规划方法,包括以下步骤:As shown in Figure 1, a UAV emergency communication path planning method includes the following steps:

步骤1.对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,在所述网格图上标注无人机的起始点和目标点,以及标注无人机飞行空间内的雷达分布和地形信息;Step 1. Carry out three-dimensional grid division on the flying space of the UAV, obtain grid nodes, construct a grid diagram, mark the starting point and target point of the UAV on the grid diagram, and mark the flight of the UAV Radar distribution and terrain information in space;

步骤2.根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时根据无人机的飞行技术参数构建飞行限定模型;Step 2. Construct a flight threat model according to the radar distribution and terrain information in the flight space of the UAV, and construct a flight limitation model according to the flight technical parameters of the UAV;

步骤3.根据飞行威胁模型和飞行限定模型在无人机的起始点和目标点之间构建飞行路线;Step 3. Construct a flight route between the starting point and the target point of the drone according to the flight threat model and the flight limitation model;

步骤4.通过混沌遗传算法对飞行路线进行优化,得最终飞行路线。Step 4. Optimizing the flight route through the chaotic genetic algorithm to obtain the final flight route.

优选的,所述飞行威胁模型具体为:Preferably, the flight threat model is specifically:

min W=k1Jthreat+k2Jfuelmin W=k 1 J threat +k 2 J fuel ;

其中Jthreat为雷达威胁代价,k1(k1∈(0,1))为雷达威胁代价的权重,Jfuel为燃油代价,k2(k2∈(0,1))为燃油代价的权重;雷达威胁代价为无人机飞行高度的限定,飞行高度超过设定高度,容易被雷达侦查到,存在被跟踪的风险,是无人机需要避规的;燃油代价为无人机自身负载燃油的重量,满足无人机往返飞行的燃油需求,飞行距离过长,易造成无人机无法返回,是无人机需要规避的。Where J threat is radar threat cost, k 1 (k 1 ∈ (0, 1)) is the weight of radar threat cost, J fuel is fuel cost, k 2 (k 2 ∈ (0, 1)) is the weight of fuel cost ; The radar threat cost is the limitation of the flying height of the UAV. If the flying height exceeds the set height, it is easy to be detected by the radar, and there is a risk of being tracked, which is what the UAV needs to avoid. The fuel cost is the fuel loaded by the UAV itself. The weight of the drone can meet the fuel demand for the round-trip flight of the UAV. If the flight distance is too long, it will easily cause the UAV to fail to return, which is what the UAV needs to avoid.

优选的,所述飞行限定模型包括:Preferably, the flight-limited model includes:

无人机在改变姿态时直飞的距离r小于无人机的起始点至目标点之间的距离Smin,r<SminThe direct flight distance r of the UAV when changing the attitude is smaller than the distance S min between the starting point and the target point of the UAV, and r<S min .

优选的,所述飞行限定模型包括:Preferably, the flight-limited model includes:

无人机在探测到障碍物时悬停的时间Tmin小于无人机飞行的总时长t,Tmin<t。The hovering time T min of the UAV when an obstacle is detected is less than the total flight time t of the UAV, and T min < t.

优选的,所述飞行限定模型包括:Preferably, the flight-limited model includes:

飞行路线的高度H大于无人机飞行设定的最低飞行高度Hmin,且小于无人机飞行设定的最高飞行高度Hmax,Hmin<H<HmaxThe altitude H of the flight route is greater than the minimum flight altitude H min set for the drone flight, and smaller than the maximum flight altitude H max set for the drone flight, and H min <H<H max .

优选的,所述飞行限定模型包括:Preferably, the flight-limited model includes:

飞行路线的距离L小于无人机飞行极限距离的二分之一,L<Lmax/2。The distance L of the flight route is less than half of the flight limit distance of the UAV, and L<L max /2.

优选的,所述飞行限定模型包括:无人机沿着x坐标轴的正方向飞行,当前所在节点的坐标为(x1,y1,z1),下一节点的坐标为(x2,y2,z2),无人机在水平方向和垂直方向偏转的最大角度Ф满足:Preferably, the flight limitation model includes: the UAV flies along the positive direction of the x coordinate axis, the coordinates of the current node are (x1, y1, z1), and the coordinates of the next node are (x2, y2, z2) , the maximum deflection angle Ф of the UAV in the horizontal direction and vertical direction satisfies:

|| arctanarctan (( ythe y 22 -- ythe y 11 xx 22 -- xx 11 )) || &le;&le; &phi;&phi; mm aa xx || arctanarctan (( zz 22 -- zz 11 xx 22 -- xx 11 )) || &le;&le; &gamma;&gamma; mm aa xx ;;

其中Фmax为无人机水平方向偏转的极限角度;уmax为无人机垂直方向偏转的极限角度。Among them, Ф max is the limit angle of UAV horizontal deflection; у max is the limit angle of UAV vertical deflection.

优选的,通过混沌遗传算法对飞行路线进行优化具体包括以下步骤:Preferably, optimizing the flight route through the chaotic genetic algorithm specifically includes the following steps:

步骤4.1.利用混沌运动Logistic映射方程xk+1=uxk(1-xk)(1),随机生成初始混沌序列,其中u是控制参数,当u=4时,上式完全处于混沌状态,且在[0,1]内是遍历的;Step 4.1. Use the chaotic motion Logistic mapping equation x k+1 =ux k (1-x k )(1) to randomly generate the initial chaotic sequence, where u is the control parameter. When u=4, the above formula is completely in a chaotic state , and it is traversed within [0,1];

步骤4.2.将一次产生的混沌变量XK按(2)式映射成新的混沌变量X,同时将整个遍历区间[0,1]映射到优化变量的取值区间[a,b];Step 4.2. Map the chaotic variable X K generated once into a new chaotic variable X according to formula (2), and map the entire traversal interval [0,1] to the value interval [a,b] of the optimized variable at the same time;

Xx == aa ++ xx ii kk (( bb -- aa )) -- -- -- (( 22 )) ;;

步骤4.3.利用所述混沌变量,进行混沌搜索;Step 4.3. Use the chaotic variable to perform chaotic search;

通过混沌发生器产生的随机步长在无人机执行任务的区间范围[a,b]内对飞行路线进行扰动,同时飞行路线实时根据目标点和初始点连线的偏离程度Li以及无人机距离威胁的最近距离Ci,计算飞行路线中路段个体的适值f(X),得到路段个体的适值由高到低进行排序,对适值低的10%路段个体进行淘汰,剩下适值高的90%路段个体;The random step size generated by the chaos generator disturbs the flight route within the range [a,b] of the drone’s mission, and the flight route is based on the deviation degree L i of the target point and the initial point in real time and the unmanned Calculate the fitness value f(X) of the road section individuals in the flight route, and sort the fitness values of the road section individuals from high to low, and eliminate 10% of the road section individuals with low fitness values, leaving the high fitness values 90% of individual road sections;

步骤4.4.循环步骤4.1至步骤4.3直到路段个体数量达到设定规模,组合成初始种群;Step 4.4. Repeat steps 4.1 to 4.3 until the number of individuals in the road section reaches the set scale, and combine them into an initial population;

步骤4.5.在初始种群中适值高的90%个体中随机选择两个配对个体,按混沌交叉规律进行交叉操作;Step 4.5. Randomly select two paired individuals among the 90% individuals with high fitness in the initial population, and perform the crossover operation according to the chaotic crossover rule;

步骤4.6.将配对个体按混沌变异规律进行变异操作,得多个变异个体,将多个变异个体与初始种群中适值排序中前10%的个体进行合并构成二代种群;Step 4.6. The paired individuals are mutated according to the law of chaotic variation to obtain multiple mutated individuals, and the multiple mutated individuals are combined with the top 10% individuals in the initial population to form the second generation population;

步骤4.7.对二代群体中两个相同个体中的一个进行删除,同时对二代种群中适值排序中后10%的个体进行淘汰,得二代种群中适值高的90%个体;Step 4.7. Delete one of the two identical individuals in the second-generation population, and eliminate the bottom 10% individuals in the second-generation population in the fitness ranking, and obtain 90% of individuals with higher fitness in the second-generation population;

步骤4.8.对二代种群中适值高的90%个体进行混沌遗传操作,生成多个遗传个体,并构成遗传种群,将遗传种群中适值低的90%个体进行淘汰,得遗传种群中适值高的10%个体;Step 4.8. Perform chaotic genetic operations on 90% of the individuals with high fitness in the second generation population, generate multiple genetic individuals, and form a genetic population, eliminate 90% of the individuals with low fitness in the genetic population, and obtain the genetic population with high fitness 10% individual;

步骤4.9.将遗传种群中适值高的10%个体进行解码,规划得出最终的无人机飞行路径。Step 4.9. Decode the 10% individuals with high fitness in the genetic population, and plan to obtain the final UAV flight path.

路段个体为整个飞行路线中的一个飞行路段,作为混沌遗传算法中的基因;The segment individual is a flight segment in the entire flight route, which is used as the gene in the chaotic genetic algorithm;

混沌交叉确定操作:选择区间在进行交叉操作时,选出的两个配对个体,根据xk+1=uxk(1-xk),所产生的一个独立混沌序列的当前值xk1确定其是否进行交叉,若xk1∈Pc则进行交叉操作,否则,不进行交叉。Chaotic intersection determination operation: selection interval When performing the crossover operation, the selected two pairs of individuals, according to x k+1 = ux k (1-x k ), determine whether to perform crossover by the current value x k1 of an independent chaotic sequence generated, if x k1 ∈P c then carry out crossover operation, otherwise, do not carry out crossover.

交叉位的确定,将线路个体作为基因,根据基因中染色体的长度,将其分为若干段,可以几位或1位为一段,同时将区间(0,1)也分为若干子区间,其中每个子区间分别对应染色体中的一个段,对于需要进行交叉操作的个体,根据xk+1=uxk(1-xk),产生的另一个独立混沌序列的当前值xk2所属的子区间来确定进行交叉操作基因段的位置;To determine the cross position, the line individual is used as a gene, and according to the length of the chromosome in the gene, it is divided into several segments, which can be several bits or 1 bit, and the interval (0,1) is also divided into several sub-intervals, among which Each subinterval corresponds to a segment in the chromosome. For individuals that need to perform crossover operations, according to x k+1 = ux k (1-x k ), the subinterval to which the current value x k2 of another independent chaotic sequence belongs To determine the position of the gene segment for crossover operation;

将所选定的两个染色体相应基因段进行交换,产生两个新个体,从而完成混沌交叉;Exchange the corresponding gene segments of the two selected chromosomes to generate two new individuals, thus completing the chaotic crossover;

混沌变异操作:变异的确定,与交叉的确定方法一样,只是变异区间Pm一般应小于交叉区间Pc,只有当混沌序列的当前值xk3∈Pm,才进行变异操作;Chaos mutation operation: the determination of mutation is the same as the determination method of crossover, except that the variation interval P m should generally be smaller than the intersection interval P c , and only when the current value of the chaotic sequence x k3 ∈ P m , the mutation operation is performed;

变异位的确定,将区间(0,1)作N等分,其中N为染色体的长度,再根据混沌序列当前值xk4所处的子区间确定变异的基因位置;For the determination of the mutated bit, divide the interval (0,1) into N equal parts, where N is the length of the chromosome, and then determine the mutated gene position according to the sub-interval where the current value x k4 of the chaotic sequence is located;

对经过混沌交叉产生的配对个体,按混沌变异规律进行变异操作;xi为变异操作前的第i个个体,它对应一个由N的分量组成的向量,xi(j)为第j个分量,x′i(j)为变异后的第i个个体的第j个分量,σi(j)为第j个分量近似的变异尺度,采用混沌变异形式如下:For the paired individuals generated by chaotic crossover, the mutation operation is performed according to the law of chaotic mutation; x i is the i-th individual before the mutation operation, which corresponds to a vector composed of N components, and x i (j) is the j-th component , x′ i (j) is the jth component of the ith individual after mutation, σi (j) is the approximate variation scale of the jth component, and the chaotic variation form is as follows:

x′i(j)=xi(j)+σi(j)Kj(0,1);其中K(0,1)为混沌规律变化的序列。x' i (j) = x i (j) + σ i (j) K j (0, 1); where K (0, 1) is a sequence of changes in the law of chaos.

将经上述操作得到的变异个体,将多个变异个体与初始种群中适值高的10%个体合并构成二代种群,同时对群体中相同个体进行过滤操作,保留其中一个,而对与之相同或相似的其它个体进行概率较大范围内的混沌变异操作,以保证群体的多样性,避免算法陷入局部极小。For the mutant individuals obtained through the above operations, multiple mutant individuals are combined with 10% individuals with high fitness values in the initial population to form a second-generation population. Other similar individuals perform chaotic mutation operations in a large range of probability to ensure the diversity of the group and avoid the algorithm from falling into a local minimum.

优选的,适值计算具体为:Preferably, the fitness value calculation is specifically:

ff (( Xx )) == &Sigma;&Sigma; ii == 11 NN -- 11 LL ii (( NN -- ii )) ** dd 00 ** 1010 dd ii ,, minmin ** ll ii (( Xx ii )) ** CC ii ;;

其中是路径偏离目标点与初始点连线的偏离程度惩罚系数;in is the penalty coefficient for the degree of deviation of the path from the line connecting the target point and the initial point;

Li是第i路径点到目标点的距离,d0为航路段的长度,通常根据无人机的导航方式确定,Li is the distance from the i-th path point to the target point, and d0 is the length of the route segment, which is usually determined according to the navigation method of the UAV.

(N-i)*d0是沿着初始点与目标连线方向的距离,li是路径段的实际距离;其中是安全性的惩罚系数;(Ni)*d0 is the distance along the direction of the initial point and the target line, l i is the actual distance of the path segment; where is the security penalty coefficient;

di,min是第i路径段路径距离威胁的最近距离,Ci为路径的目标点与其前一点之间的偏转角满足约束的惩罚系数。di, min is the shortest distance between the i-th path segment and the threat, and C i is the penalty coefficient that the deflection angle between the target point of the path and its previous point satisfies the constraint.

如图2所示,一种无人机应急通信路径规划系统,包括:As shown in Figure 2, a UAV emergency communication path planning system includes:

划分模块1,用于对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,在所述网格图上标注无人机的起始点和目标点,以及标注无人机飞行空间内的雷达分布和地形信息;The division module 1 is used for performing three-dimensional grid division on the flying space of the drone, obtaining grid nodes, constructing a grid map, marking the starting point and the target point of the drone on the grid map, and marking the unmanned aerial vehicles. Radar distribution and terrain information in the man-machine flight space;

建模模块2,用于根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时根据无人机的飞行技术参数构建飞行限定模型;The modeling module 2 is used to construct a flight threat model according to the radar distribution and terrain information in the flight space of the UAV, and to construct a flight limitation model according to the flight technical parameters of the UAV;

构建路线模块3,用于根据飞行威胁模型和飞行限定模型在无人机的起始点和目标点之间构建飞行路线;Construct route module 3, be used for constructing flight route between the starting point and target point of unmanned aerial vehicle according to flight threat model and flight restriction model;

筛选模块4,用于通过混沌遗传算法对飞行路线进行筛选,得确定飞行路线。The screening module 4 is used to screen the flight route through the chaotic genetic algorithm to determine the flight route.

混沌遗传算法对飞行路线进行优化的具体实现:The specific implementation of chaotic genetic algorithm to optimize the flight route:

对系统参数进行初始化:混沌变量的xk初值为0.2;无人机飞行任务的区间范围a,b的初始值为a=0,b=2000m;取当前最长飞行距离为=2000m;令一次载波迭代次数k初值为0,循环次数i=1;将混沌变量的初值x0代入xk+1=4xk(1-xk),进行迭代运算,并将上式得到的代入xk+1代入得到无人机飞行的目标点与初始点连线的偏离程度X,令k=k+1;Initialize the system parameters: the initial value of x k of the chaotic variable is 0.2; the initial value of the range a and b of the UAV flight task is a=0, b=2000m; the current longest flight distance is =2000m; The initial value of the number of carrier iteration k is 0, and the number of cycles i=1; the initial value x 0 of the chaotic variable is substituted into x k+1 = 4x k (1-x k ), and the iterative operation is performed, and the value obtained by the above formula is substituted into x k+1 substitute Obtain the degree of deviation X between the target point and the initial point of the UAV flight, let k=k+1;

计算无人机飞行路径的适值;Calculate the fitness value of the flight path of the UAV;

无人机飞行路径距离是否大于无人机飞行距离预测的2000m,如果是,则将无人机飞行距离的值赋给人机飞行距离预测的最大值;如果否,则执行i=i+1;Whether the flight path distance of the drone is greater than the 2000m predicted by the flight distance of the drone, if yes, assign the value of the flight distance of the drone to the maximum value of the flight distance prediction of the drone; if not, execute i=i+1 ;

判断循环次数i是否大于20或者一次载波的混沌变量迭代次数k是否大于迭代次数100,如果是,计算飞行路径中每一条路径的适值,得到的路径适值由高到低进行排序,对适值低的10%个体进行淘汰,剩下适值高的90%个体;如果否,则将混沌变量的初值x0代入xk+1=4xk(1-xk)进行迭代运算,继而进行循环。Judging whether the number of cycles i is greater than 20 or whether the number of iterations k of the chaotic variable of a carrier is greater than the number of iterations 100, if so, calculate the fitness value of each path in the flight path, and sort the fitness values of the obtained paths from high to low, and for the low fitness value 10% of individuals are eliminated, leaving 90% of individuals with high fitness; if not, the initial value x 0 of the chaotic variable is substituted into x k+1 = 4x k (1-x k ) for iterative operation, and then the cycle is performed.

以上所述仅为本发明的较佳实施例,并不用以限制本发明,凡在本发明的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection of the present invention. within range.

以上所述仅为本发明的较佳实施例,并不用以限制本发明,凡在本发明的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection of the present invention. within range.

Claims (10)

1.一种无人机应急通信路径规划方法,其特征在于,包括以下步骤:1. A UAV emergency communication path planning method, is characterized in that, comprises the following steps: 步骤1.对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,在所述网格图上标注无人机的起始点和目标点,以及标注无人机飞行空间内的雷达分布和地形信息;Step 1. Carry out three-dimensional grid division on the flying space of the UAV, obtain grid nodes, construct a grid diagram, mark the starting point and target point of the UAV on the grid diagram, and mark the flight of the UAV Radar distribution and terrain information in space; 步骤2.根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时根据无人机的飞行技术参数构建飞行限定模型;Step 2. Construct a flight threat model according to the radar distribution and terrain information in the flight space of the UAV, and construct a flight limitation model according to the flight technical parameters of the UAV; 步骤3.根据飞行威胁模型和飞行限定模型在无人机的起始点和目标点之间构建飞行路线;Step 3. Construct a flight route between the starting point and the target point of the drone according to the flight threat model and the flight limitation model; 步骤4.通过混沌遗传算法对飞行路线进行优化,确定最终飞行路线。Step 4. Optimizing the flight route through the chaotic genetic algorithm to determine the final flight route. 2.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,所述飞行威胁模型具体为:min W=k1Jthreat+k2Jfuel2. A kind of unmanned aerial vehicle emergency communication route planning method according to claim 1, is characterized in that, described flight threat model is specifically: min W=k 1 J threat +k 2 J fuel ; 其中Jthreat为雷达威胁代价,k1(k1∈(0,1))为雷达威胁代价的权重,Jfuel为燃油代价,k2(k2∈(0,1))为燃油代价的权重。Where J threat is radar threat cost, k 1 (k 1 ∈ (0, 1)) is the weight of radar threat cost, J fuel is fuel cost, k 2 (k 2 ∈ (0, 1)) is the weight of fuel cost . 3.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,所述飞行限定模型包括:3. A kind of unmanned aerial vehicle emergency communication route planning method according to claim 1, is characterized in that, described flight limitation model comprises: 无人机在遇到障碍物时改变姿态直飞的距离r小于无人机的起始点至障碍点之间的距离Smin,r<SminWhen the UAV encounters an obstacle, the distance r from which the UAV changes its attitude and flies straight is less than the distance S min between the starting point of the UAV and the obstacle point, and r<S min . 4.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,所述飞行限定模型包括:4. A kind of unmanned aerial vehicle emergency communication path planning method according to claim 1, is characterized in that, described flight limitation model comprises: 无人机在检测到障碍物时悬停的时间t大于无人机控制响应的最短时长Tmin,Tmin<t。The hovering time t of the UAV when an obstacle is detected is greater than the shortest duration T min of the UAV control response, and T min <t. 5.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,所述飞行限定模型包括:5. A kind of unmanned aerial vehicle emergency communication path planning method according to claim 1, is characterized in that, described flight limitation model comprises: 飞行路线的高度H大于无人机飞行设定的最低飞行高度Hmin,且小于无人机飞行设定的最高飞行高度Hmax,Hmin<H<HmaxThe altitude H of the flight route is greater than the minimum flight altitude H min set for the drone flight, and smaller than the maximum flight altitude H max set for the drone flight, and H min <H<H max . 6.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,所述飞行限定模型包括:6. A kind of unmanned aerial vehicle emergency communication path planning method according to claim 1, is characterized in that, described flight limitation model comprises: 飞行路线的距离L小于无人机飞行极限距离的二分之一,L<Lmax/2。The distance L of the flight route is less than half of the flight limit distance of the UAV, and L<L max /2. 7.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,所述飞行限定模型包括:无人机沿着x坐标轴的正方向飞行,当前所在节点的坐标为(x1,y1,z1),下一节点的坐标为(x2,y2,z2),无人机在水平方向和垂直方向偏转的最大角度Ф满足:7. A kind of unmanned aerial vehicle emergency communication path planning method according to claim 1, is characterized in that, described flight limitation model comprises: unmanned aerial vehicle flies along the positive direction of x coordinate axis, and the coordinate of current location node is ( x1, y1, z1), the coordinates of the next node are (x2, y2, z2), the maximum deflection angle Ф of the drone in the horizontal and vertical directions satisfies: || arctanarctan (( ythe y 22 -- ythe y 11 xx 22 -- xx 11 )) || &le;&le; &phi;&phi; mm aa xx || arctanarctan (( zz 22 -- zz 11 xx 22 -- xx 11 )) || &le;&le; &gamma;&gamma; mm aa xx ;; 其中Фmax为无人机水平方向偏转的极限角度;уmax为无人机垂直方向偏转的极限角度。Among them, Ф max is the limit angle of UAV horizontal deflection; у max is the limit angle of UAV vertical deflection. 8.根据权利要求1所述一种无人机应急通信路径规划方法,其特征在于,通过混沌遗传算法对飞行路线进行优化具体包括以下步骤:8. A kind of unmanned aerial vehicle emergency communication path planning method according to claim 1, is characterized in that, optimizes flight route by chaotic genetic algorithm and specifically comprises the following steps: 步骤4.1.利用混沌运动Logistic映射方程xk+1=uxk(1-xk) (1),随机生成初始混沌序列,其中u是控制参数,当u=4时,上式完全处于混沌状态,且在[0,1]内是遍历的;Step 4.1. Use the chaotic motion Logistic mapping equation x k+1 = ux k (1-x k ) (1) to randomly generate the initial chaotic sequence, where u is the control parameter. When u=4, the above formula is completely in a chaotic state , and it is traversed within [0,1]; 步骤4.2.将一次产生的混沌变量XK按(2)式映射成新的混沌变量X,同时将整个遍历区间[0,1]映射到优化变量的取值区间[a,b];Step 4.2. Map the chaotic variable X K generated once into a new chaotic variable X according to formula (2), and map the entire traversal interval [0,1] to the value interval [a,b] of the optimized variable at the same time; Xx == aa ++ xx ii kk (( bb -- aa )) -- -- -- (( 22 )) 步骤4.3.利用所述混沌变量,进行混沌搜索;Step 4.3. Use the chaotic variable to perform chaotic search; 通过混沌发生器产生的随机步长在无人机执行任务的区间范围[a,b]内对飞行路线进行扰动,同时飞行路线实时根据目标点和初始点连线的偏离程度Li以及无人机距离威胁的最近距离Ci,计算飞行路线中路段个体的适值f(X),得到路段个体的适值由高到低进行排序,对适值低的10%路段个体进行淘汰,剩下适值高的90%路段个体;The random step size generated by the chaos generator disturbs the flight route within the range [a,b] of the drone’s mission, and the flight route is based on the deviation degree L i of the target point and the initial point in real time and the unmanned Calculate the fitness value f(X) of the road section individuals in the flight route, and sort the fitness values of the road section individuals from high to low, and eliminate 10% of the road section individuals with low fitness values, leaving the high fitness values 90% of individual road sections; 步骤4.4.循环步骤4.1至步骤4.3直到路段个体数量达到设定规模,组合成初始种群;Step 4.4. Repeat steps 4.1 to 4.3 until the number of individuals in the road section reaches the set scale, and combine them into an initial population; 步骤4.5.在初始种群中适值高的90%个体中随机选择两个配对个体,按混沌交叉规律进行交叉操作;Step 4.5. Randomly select two paired individuals among the 90% individuals with high fitness in the initial population, and perform the crossover operation according to the chaotic crossover rule; 步骤4.6.将配对个体按混沌变异规律进行变异操作,得多个变异个体,将多个变异个体与初始种群中适值排序中前10%的个体进行合并构成二代种群;Step 4.6. The paired individuals are mutated according to the law of chaotic variation to obtain multiple mutated individuals, and the multiple mutated individuals are combined with the top 10% individuals in the initial population to form the second generation population; 步骤4.7.对二代群体中两个相同个体中的一个进行删除,同时对二代种群中适值排序中后10%的个体进行淘汰,得二代种群中适值高的90%个体;Step 4.7. Delete one of the two identical individuals in the second-generation population, and eliminate the bottom 10% individuals in the second-generation population in the order of fitness, so as to obtain 90% of individuals with high fitness in the second-generation population; 步骤4.8.对二代种群中适值高的90%个体进行混沌遗传操作,生成多个遗传个体,并构成遗传种群,将遗传种群中适值低的90%个体进行淘汰,得遗传种群中适值高的10%个体;Step 4.8. Perform chaotic genetic operations on 90% of individuals with high fitness in the second generation population to generate multiple genetic individuals to form a genetic population, eliminate 90% of individuals with low fitness in the genetic population, and obtain high fitness in the genetic population 10% individual; 步骤4.9.将遗传种群中适值高的10%个体进行解码,规划得出最终的无人机飞行路径。Step 4.9. Decode the 10% individuals with high fitness in the genetic population, and plan to obtain the final UAV flight path. 9.根据权利要求8所述一种无人机应急通信路径规划方法,其特征在于,适值计算具体为:9. A kind of unmanned aerial vehicle emergency communication route planning method according to claim 8, is characterized in that, fitness calculation is specifically: ff (( Xx )) == &Sigma;&Sigma; ii == 11 NN -- 11 LL ii (( NN -- ii )) ** dd 00 ** 1010 dd ii ,, minmin ** ll ii (( Xx ii )) ** CC ii ;; 其中是路径偏离目标点与初始点连线的偏离程度惩罚系数;in is the penalty coefficient for the degree of deviation of the path from the line connecting the target point and the initial point; Li是第i路径点到目标点的距离,d0为航路段的长度,通常根据无人机的导航方式确定;Li is the distance from the i-th path point to the target point, and d0 is the length of the route segment, which is usually determined according to the navigation method of the UAV; (N-i)*d0是沿着初始点与目标连线方向的距离,li是路径段的实际距离;其中是安全性的惩罚系数;(Ni)*d0 is the distance along the direction of the initial point and the target line, l i is the actual distance of the path segment; where is the security penalty coefficient; di,min是第i路径段路径距离威胁的最近距离,Ci为路径的目标点与其前一点之间的偏转角满足约束的惩罚系数。di, min is the shortest distance between the i-th path segment and the threat, and C i is the penalty coefficient that the deflection angle between the target point of the path and its previous point satisfies the constraint. 10.一种无人机应急通信路径规划系统,其特征在于,包括:10. A UAV emergency communication path planning system, characterized in that it comprises: 划分模块(1),用于对无人机飞行的空间进行三维网格划分,得网格节点,构建网格图,在所述网格图上标注无人机的起始点和目标点,以及标注无人机飞行空间内的雷达分布和地形信息;The division module (1) is used for carrying out three-dimensional grid division to the flying space of the unmanned aerial vehicle, obtains the grid node, constructs the grid diagram, marks the starting point and the target point of the unmanned aerial vehicle on the described grid diagram, and Mark the radar distribution and terrain information in the UAV flight space; 建模模块(2),用于根据无人机飞行空间内的雷达分布和地形信息构建飞行威胁模型,同时根据无人机的飞行技术参数构建飞行限定模型;The modeling module (2) is used to construct a flight threat model according to the radar distribution and terrain information in the flight space of the UAV, and simultaneously constructs a flight limitation model according to the flight technical parameters of the UAV; 构建路线模块(3),用于根据飞行威胁模型和飞行限定模型在无人机的起始点和目标点之间构建飞行路线;Construct route module (3), be used for constructing flight route between the starting point and target point of unmanned aerial vehicle according to flight threat model and flight restriction model; 筛选模块(4),用于通过混沌遗传算法对飞行路线进行筛选,得确定飞行路线。The screening module (4) is used to screen the flight route through the chaotic genetic algorithm to determine the flight route.
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