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LOS/NLOS混合环境中基于交互式多模型的鲁棒目标跟踪
引用本文:欧阳宁烽,周 彦,徐建闽.LOS/NLOS混合环境中基于交互式多模型的鲁棒目标跟踪[J].计算机应用研究,2013,30(11):3465-3468.
作者姓名:欧阳宁烽  周 彦  徐建闽
作者单位:1. 湘潭大学 信息工程学院, 湖南 湘潭 411105; 2. 华南理工大学 土木工程与交通学院, 广州 510640
基金项目:国家自然科学基金资助项目(61104210, 6110140)
摘    要:针对视距(line-of-sight, LOS)和非视距(none-line-of-sight, NLOS)混合环境的定位跟踪问题, 提出一种基于扩展H∞滤波(EHF)和扩展卡尔曼滤波(EKF)的交互式多模型(IMM)定位跟踪算法。目标与基站之间的LOS、NLOS传输信道分别用EKF和EHF匹配, 模型间的转换用马尔可夫过程进行描述。Monte Carlo仿真结果表明, 该算法具有较高的定位精度、较好的跟踪稳定性, 且计算时间与基于EKF的IMM算法相当, 具有较好的可实现性。

关 键 词:目标跟踪  扩展H∞滤波  扩展卡尔曼滤波  交互式多模型  LOS/NLOS混合环境

Robust target tracking in LOS/NLOS hybrid environmentbased on interactive multiple model
OUYANG Ning-feng,ZHOU Yan,XU Jian-min.Robust target tracking in LOS/NLOS hybrid environmentbased on interactive multiple model[J].Application Research of Computers,2013,30(11):3465-3468.
Authors:OUYANG Ning-feng  ZHOU Yan  XU Jian-min
Affiliation:1. College of Information Engineering, Xiangtan University, Xiangtan Hunan 411105, China; 2. School of Civil Engineering & Transportation, South China University of Technology, Guangzhou 510640, China
Abstract:To attack the location and tracking problem in LOS/NLOS hybrid environment, this paper proposed a robust interactive multiple model approach based on extended H-infinity filter (EHF) and extended Kalman filter (EKF). It matched the LOS and NLOS transmission channels between the base station and target by EKF and EHF, respectively. Then, it described the mode transmission between EKF and EHF by a Markov process. Monte Carlo simulation results show that the algorithm has higher positioning accuracy, better tracking stability and similar computing complex compared with the interactive multiple model method based on EKF.
Keywords:target tracking  extended H-infinity filter  extended Kalman filter(EKF)  interacting multiple model(IMM)  LOS/NLOS hybrid environment
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