Robust ML-estimation of the Transmitter Location

Location of a radio transmitter may be estimated using the triangulation principle and angular measurements from at least two sensor arrays. For example, two base-stations equipped with antenna arrays observe the waveforms emitted by a transmitter such as a mobile phone. Based on the estimates of angle-of-arrival (AoA) of waveforms impinging the antenna array at base-stations, an estimate of the location of the transmitter can be formed using elemental geometry. In this paper, we discuss the ML-estimation of the location of the transmitter by modelling the distribution of the AoAs by two well-known angular distributions, namely the von Mises and the wrapped Cauchy distribution. These distributions are well justified by the physical measurements on radio wave propagation. Since the received signals at the base-stations are corrupted by noise which may be impulsive in nature, robust estimation of the signal parameters is an important issue.