Source Localization in Sensor Networks with Rayleigh Faded Signals

Source localization is investigated for a sensor network with passive sensors. The signal emitted by the source endures Rayleigh fading during its propagation, and its average intensity is a function of the distance from the source. Maximum likelihood (ML) source location estimators that use the output, or its quantized version, of the non-coherent receiver is proposed. The ML estimators' Cramer-Rao lower bounds (CRLBs) are derived. Due to the fading effect, the proposed estimator's performance is degraded, compared to the ideal case without fading. However, it can still accurately estimate the source's position and intensity, and achieve its CRLB with relatively small amount of resources, namely small number of observations, sensors and quantization bits.