基于遗传算法的无人机纯方位无源定位

Pure Azimuthal Passive Localization of UAV Based on Genetic Algorithm

摘要: 为直观表示圆形编队无人机集群中各个无人机之间的相对位置，和便于后续问题的解决。我们分析了无人机之间的几何关系，将圆环上发射信号无人机的位置关系分为四类，并建立纯方位无源定位模型，以3架发射信号无人机之间连线的弦、方向角为圆周角确定3个圆，这3个圆的交点中距离待测无人机理想位置最短的，便是待定位无人机的实际位置。然后为明确无人机理想位置和实际位置的差距，我们建立偏差度指标，实现对无人机编队定位误差的形容。并在每次调整中，我们选择偏差度较小的无人机作为发射信号无人机。最后我们通过使用基于遗传算法改进的迭代法进行计算，经历14次调整后，我们发现无人机总体的平均偏差值变化十分平缓，所以认为此时已经达到较好的调整方案。

Abstract: In order to intuitively represent the relative position of each UAV in the circular formation UAV cluster, and to facilitate the solution of subsequent problems. We analyze the geometric relation-ship between drones, the ring on the ring is divided into four categories, and establish a pure ori-entation passive positioning model, with three transmit signal drones connection between the string, direction Angle to determine three circles, the three circles in the intersection distance to test the shortest ideal position, is the actual position of the UAV. Then, in order to clarify the gap between the ideal and actual position of UAV, we establish the deviation index to realize the de-scription of UAV formation positioning error. And in each adjustment, we choose the UAV with less deviation as the transmit signal UAV. Finally, we used the improved iterative method based on the genetic algorithm. After 14 adjustments, we found that the average deviation value of the UAV overall changed very gently, so we thought that a better adjustment scheme had been achieved at this time.