Application of Particle Swarm Optimization with Stochastic Inertia Weight and Adaptive Mutation in Target Localization

摘要：

Target localization based on time difference of arrival (TDOA) measurements has important applications in sonar, radar and sensor networks. This paper simply imtroduced the target localization principle of moving emitter and the position location algorithm. Further more presented an improved particle swarm optimization with stochastic inertia weight and adaptive mutation, and adopts it to solve the target localization problem according to the batch of continuous TDOA measurements. The experimental results show that the new algorithm has higher localization accuracy, better algorithm stability and faster convergence rate.

关键词： time difference localization particle swarm optimization stochastic inertia weight adaptive mutation

作者: Jinjie Yao Jinxiao Pan Yan Han Liming Wang

作者单位: National Key Laboratory of Electronic Testing Technology North University of China Taiyuan, 030051, National Key Laboratory of Ministry of Education North University of China Taiyuan,030051, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 251-254

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）