基于二进制粒子群算法的植保无人机跟踪

Plant Protection Unmanned Aerial Vehicle Tracking Based on Binary Particle Swarm Optimization Algorithm

针对粒子群算法跟踪植保无人机效果差问题,提出了基于二进制粒子群算法的解决方案,把粒子位置被限制为0或1,对应植保无人机跟踪过程中的跟踪与未跟踪状态,sigmoid函数将粒子的速度转换到区间[0,1]上,并且修正粒子的位置,建立植保无人机进行机动模型和跟踪模型,构造参量加权最小二乘目标函数对跟踪测量。计算机仿真表明,该方法跟踪状态与真实状态偏差较小,数值波动较小且趋于稳定时间较短,跟踪虚警率低。

Aiming at the poor tracking effect of particle swarm optimization(PSO)algorithm for plant protection UAV,a solution based on Binary Particle Swarm Optimization(BPSO)is proposed.The particle position is limited to 0 or 1,and the sigmoid function converts the particle velocity into the interval[0,1]corresponding to the Tracking and Not Tracking state in the process of plant protection UAV tracking.In addition,the position of the particle is modified,and the maneuvering model and tracking model of the plant protection UAV are established.The computer simulation shows that the tracking state has a small deviation from the real state,the numerical fluctuation is small,and the time to stabilize is short,and the tracking false alarm rate is low.