基于粒子滤波的无人机协同跟踪算法  

Study on Cooperative Tracking Algorithm Based on Particle Filter for UAVs

作　　者：姜肖英[1] 姚敏[1] 赵敏[1] 

机构地区：[1]南京航空航天大学自动化学院,南京210016

出　　处：《火力与指挥控制》2012年第11期156-158,共3页Fire Control & Command Control

基　　金：航空科学基金(2009ZC52041);南京航空航天大学基本科研业务费专项研究基金资助项目(NP2011005)

摘　　要：针对无人机群协同跟踪移动目标问题展开研究。由于传感器测量精度的有限性,采用多架无人机合作来获得多个测量值,再根据数据融合的方法获得较精确的测量值;建立了移动目标的模型,结合测量值应用粒子滤波算法来预测目标的状态。仿真结果表明了该算法能使无人机获得较好的跟踪效果。This paper investigates the cooperative tracking a moving target by using unmanned aerial vehicles （UAV） . Because of the limited nature of the sensor accuracy, it uses Establishing multi-UAV to obtain multiple measurements, according to data fusion method to obtain more accurate measurements. A model of a moving target, then using particle filter to predict the target state is established. The results of the simulation tests prove that this method can keep tracking the moving targets well for UAV.

关 键 词：协同跟踪 数据融合 粒子滤波 移动目标 

分 类 号：V279[航空宇航科学与技术—飞行器设计]