Cramer Rao Lower Bound for Multi-Source Localization in Spatial Correlated Environment

This extended abstract paper provides the modeling approach and some indicative results on the expected performance of received power-based multiple source localization in spatially-correlated log-normal propagation environment. By proper modeling approximation of the received signal strength we are able to evaluate the Crammer-Rao Lower Bound (CRLB) given the positions of the sources and sensors. Probabilistic models are used for both the sensor network as well as the multiple sources and a semi-analytic approach is taken to compute the average performance lower bound. The results are indicative on the expected localization accuracy in a multi-source localization scenario, when the correlation of the propagation environment is exploited.