Performance bounds for cooperative RSS emitter tracking using diffusion particle filters

Abstract

This paper introduces a methodology for numerical computation of the Posterior Cramér-Rao Lower Bound (PCRLB) for the position estimate mean-square error when a moving emitter is tracked by a network of received-signal-strength (RSS) sensors using a distributed, random exchange diffusion filter. The square root of the PCRLB is compared to the empirical root-mean-square error curve for a particle filter implementation of the diffusion filter, referred to as RndEx-PF, and to the square root of the PCRLB for the optimal centralized filter that assimilates all network measurements at each time instant. In addition, we also compare the proposed RndEx-PF algorithm to three alternative distributed trackers based on Kullback-Leibler fusion using both iterative consensus and non-iterative diffusion strategies.