基于改进粒子滤波的无人机编队协同导航

针对主从式无人机编队协同导航问题，建立主从无人机编队的运动模型，并将闪烁噪声加入到观测模型中，使用粒子滤波算法进行仿真实验，使实验结果更具现实性。针对粒子滤波在重采样过程中出现的粒子贫化现象，在粒子权重归一化过程中引入权重影响因子，给出理论证明，并与标准粒子滤波算法进行对比。仿真结果表明：在闪烁噪声下，改进后的粒子滤波使主从式无人机编队导航精度明显提高，具有一定的实用价值。

UAV Formation Cooperative Navigation Based on Improved Particle Filter

Aiming at the co-navigation problem of master-slave UAV formation, the motion model of master-slave UAVformation is established, and the flicker noise is added to the observation model. The particle filter algorithm is used tosimulate the experiment, which makes the experimental result more realistic. Aiming at the phenomenon of particledepletion in particle re-sampling process, the weight influence factor is introduced in the process of particle weightnormalization, and the theoretical proof is given, and compared with the standard particle filter algorithm. The simulationresults show that under the flicker noise, the improved particle filter makes the navigation precision of the master-slaveUAV formation significantly improved, which has certain practical value.