We present a novel hybrid localization algorithm for wireless sensor networks in the absence of knowledge regarding the transmit power and path-loss exponent. Transmit power and the path-loss exponent are critical parameters for target localization algorithms in wireless sensor networks, which help extract target position information from the received signal strength. In the absence of information on transmit power and path-loss exponent, it is critical to estimate them for reliable deployment of conventional target localization algorithms. In this paper, we propose a simultaneous estimation of transmit power and path-loss exponent based on Kalman filter. The unknown transmit power and path-loss exponent are estimated using a Kalman filter with the tentatively estimated target position based solely on angle information. Subsequently, the target position is refined using a hybrid method incorporating received signal strength measurements based on the estimated transmit power and path-loss exponent. Our proposed algorithm accurately estimates transmit power and path-loss exponent and yields almost the same target position accuracy as the simulation results confirm, as the hybrid target localization algorithms with known transmit power and path-loss exponent. Simulation results confirm the proposed algorithm achieves 99.7% accuracy of the target localization performance with known transmit power and path-loss exponent, even in the presence of severe received signal strength measurement noise.
Bibliographical noteFunding Information:
Acknowledgments: The authors gratefully acknowledge the support from the Electronic Warfare Research Center (EWRC) at the Gwangju Institute of Science and Technology (GIST), originally funded by the Defense Acquisition Program Administration (DAPA) and Agency for Defense Development (ADD).
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Angle of arrival (AOA)
- Kalman filter (KF)
- Path-loss exponent (PLE)
- Received signal strength (RSS)
- Target localization
- Transmit power (TP)
- Wireless sensor networks (WSNs)
ASJC Scopus subject areas
- Analytical Chemistry
- Information Systems
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering