Received signal strength difference-based tracking estimation method for arbitrarily moving target in wireless sensor networks

被引:8
作者
Jia, Zixi [1 ]
Guan, Bo [2 ]
机构
[1] Northeastern Univ, Fac Robot Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL USA
来源
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | 2018年 / 14卷 / 03期
基金
中国国家自然科学基金;
关键词
Wireless sensor networks; localization; received signal strength difference; possible zone; threshold; LOCALIZATION;
D O I
10.1177/1550147718764875
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The surveillance system, which is mainly used for detecting and tracking moving targets, is one of the most significant applications of wireless sensor networks. Up to present, received signal strength indicator is the most common measuring mean for estimating the distance in sensor networks. However, in the presence of noise, it is impossible to gain the accurate distance based on received signal strength indicator. In this article, we propose a new tracking scheme based on received signal strength difference, which is the difference value of received signal strength indicators between two neighboring sampling steps. Supposing the noise has a certain degree of correlation in a certain time interval, received signal strength difference can effectively reduce the negative impact from noise. The tracking algorithm based on received signal strength difference is built: The sensor nodes collectively estimate a possible zone of the target via the signs of received signal strength difference. Next, the possible zone is further immensely shrunk to the refined zone via the absolute values of received signal strength difference. Finally, we determine the target's final location by choosing the reference dot with the minimum norm in the refined zone. The simulation results demonstrate that the proposed tracking method achieves higher localization accuracy than the typical received signal strength indicator-based scheme. The received signal strength difference-based method also has good generality and robustness with respect to the noises with different deviation values and the target following arbitrarily state model.
引用
收藏
页数:19
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