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.