Real-Time Estimation of Sensor Node's Position Using Particle Swarm Optimization With Log-Barrier Constraint

被引:59
作者
Hong Anh Nguyen [1 ]
Guo, Hao [2 ]
Low, Kay-Soon [3 ]
机构
[1] ASTAR, Inst Infocomm Res, Singapore 119613, Singapore
[2] ASM Singapore Technol, Singapore 768924, Singapore
[3] Nanyang Technol Univ, Singapore 639798, Singapore
关键词
Extended Kalman filter (EKF); log-barrier method; particle swarm optimization (PSO); position measurement; wireless sensor network (WSN); LOCALIZATION; NETWORKS; PERFORMANCE; ALGORITHM; SEQUENCE; TRACKING; FUSION;
D O I
10.1109/TIM.2011.2135030
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a new approach is proposed to estimate the location of a sensor in a wireless sensor network. For the estimation, only a few anchor nodes with known locations and received signal strength (RSS) indicator (RSSI) are needed. It is well known that the RSS reduces with increasing distance between the transceivers following a nonlinear path loss model. Most published works determine these parameters offline. This often yields limited estimation accuracy due to high variance of RSSI measurements. To improve the estimation accuracy, the parameters are estimated together with the unknown node's location in real time in this paper. To optimize the results, a new particle swarm optimization with log-barrier approach is proposed. Both simulation and experimental results show that the proposed scheme performs well as compared with some existing schemes.
引用
收藏
页码:3619 / 3628
页数:10
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