RSS-Based Target Localization With Unknown Model Parameters and Sensor Position Errors
Yanbin Zou, Huaping Liu
Abstract
This paper investigates the problem of received signal strength (RSS) based target localization with sensor position uncertainties and unknown model parameters. Transmit power and path-loss exponent (PLE) are two key parameters of the path-loss model that is critical for RSS schemes to work well. In practice, however, these parameters change dynamically and are difficult to estimate in real time. Four combinations of the two parameters are considered: both parameters are known; only one of the two is known; and both are unknown. We develop new semidefinite programming (SDP) methods to relax the nonconvex maximum likelihood estimator (MLE) problem for each case, and these methods are further optimized when sensor position uncertainties are taken into consideration. We present a comprehensive set of simulation results to compare the performance of the proposed scheme with existing methods.