Modeling of UAV path planning based on IMM under POMDP framework  

作　　者：YANG Qiming ZHANG Jiandong SHI Guoqing 

机构地区：[1]School of Electronics and Information,Northwestern Polytechnical University

出　　处：《Journal of Systems Engineering and Electronics》2019年第3期545-554,共10页系统工程与电子技术（英文版）

基　　金：supported by the Aeronautical Science Foundation of China(20135153031; 20135553035; 2017ZC53033)

摘　　要：In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle(UAV), the partially observable Markov decision process(POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model(IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy.The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target.Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.

关 键 词：PARTIALLY OBSERVABLE MARKOV decision process (POMDP) interactive multiple model (IMM) filtering path planning target tracking state transfer law 

分 类 号：N[自然科学总论]