RSS-Based Method for Sensor Localization with Unknown Transmit Power and Uncertainty in Path Loss Exponent.
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.
School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China. huangjiyan@uestc.edu.cn.|Institute of Electronic and Information Engineering in Dongguan UESTC, Dongguan 523808, China. huangjiyan@uestc.edu.cn.
Jiyan
J
Huang
Space Star Technology Co., Ltd. and State Key Laboratory of Space-Ground Integrated Information Technology, Beijing 100191, China. lp1381074@space-star.com.
Peng
P
Liu
School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China. 201422020706@std.uestc.edu.cn.
Wei
W
Lin
Department of Electronics and Information Systems, Akita Prefectural University, Akita 015-0055, Japan. guiguan@akita-pu.ac.jp.
Guan
G
Gui
cramer-rao lower bound (CRLB); path loss exponent (PLE); received signal strength (RSS); sensor localization; transmit power