RSS-based Localization in Wireless Sensor Networks with Unknown Transmit Power and Path Loss Exponent using SDP Relaxation

摘要

This paper addresses the problem of locating multiple target nodes from noisy received signal strength (RSS) measurements in wireless sensor networks (WSNs), for the case where the transmit power and the path loss exponent (PLE) are simultaneously unknown. According to the conventional path loss model, the maximum likelihood (ML) estimator is derived by solving the nonlinear and nonconvex least squares (LS) problem. To overcome the non-convexity of the ML optimization problem, we use a simple iterative procedure which is based on the semidefinite programming relaxation. Simulation results indicate that the new approach outperforms the existing ones in terms of the estimation accuracy, with the biggest difference for low-to-medium number of anchor nodes, which is the regime of interest in practical applications.