RSS-Based Method for Sensor Localization with Unknown Transmit Power and Uncertainty in Path Loss Exponent

被引:13
|
作者
Huang, Jiyan [1 ,2 ,5 ]
Liu, Peng [3 ,4 ]
Lin, Wei [1 ]
Gui, Guan [5 ]
机构
[1] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu 610054, Peoples R China
[2] Inst Elect & Informat Engn Dongguan UESTC, Dongguan 523808, Peoples R China
[3] Space Star Technol Co Ltd, Beijing 100191, Peoples R China
[4] State Key Lab Space Ground Integrated Informat Te, Beijing 100191, Peoples R China
[5] Akita Prefectural Univ, Dept Elect & Informat Syst, Akita 0150055, Japan
来源
SENSORS | 2016年 / 16卷 / 09期
关键词
sensor localization; cramer-rao lower bound (CRLB); received signal strength (RSS); transmit power; path loss exponent (PLE); LOCATION ESTIMATION; NODE LOCALIZATION;
D O I
10.3390/s16091452
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The localization of a sensor in wireless sensor networks (WSNs) has now gained considerable attention. Since the transmit power and path loss exponent (PLE) are two critical parameters in the received signal strength (RSS) localization technique, many RSS-based location methods, considering the case that both the transmit power and PLE are unknown, have been proposed in the literature. However, these methods require a search process, and cannot give a closed-form solution to sensor localization. In this paper, a novel RSS localization method with a closed-form solution based on a two-step weighted least squares estimator is proposed for the case with the unknown transmit power and uncertainty in PLE. Furthermore, the complete performance analysis of the proposed method is given in the paper. Both the theoretical variance and Cramer-Rao lower bound (CRLB) are derived. The relationships between the deterministic CRLB and the proposed stochastic CRLB are presented. The paper also proves that the proposed method can reach the stochastic CRLB.
引用
收藏
页数:20
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