Received Signal Strength (RSS) location estimation with nuisance parameters in correlated shadow fading

Received Signal Strength (RSS) geolocation is investigated under a Correlated Log Normal (CLN) model. Several parameters in the model may be unknown and we study their impact on both position estimation algorithms and the Cramer-Rao bound. Nuisance parameters in the CLN model include the pathloss exponent, the shadow fading standard deviation, and the shadow fading correlation. To estimate the user position, we compare the Steepest Descent and the Levenberg-Marquardt (LM) algorithms. Objective functions with and without weighting by the cova-riance matrix are considered. We prove from the CRLB that knowledge of the fading deviation and correlation is not needed by an optimal estimator. Results show the weighted objective function is a better metric, and that the LM algorithm converges very rapidly, nearly attaining the CRLB.