An approximate maximum-likelihood estimator for localisation using bistatic measurements

This paper discusses algorithms that can be used to estimate the position of an object by means of bistatic measurements. Some methods known from literature are compared with a new algorithm that is an approximation to a maximum-likelihood estimator for this non-linear localisation problem. Simulation results confirm that the proposed estimator yields errors close to Cramer-Rao lower bound for lower levels of measurement noise while still providing the best performance among the investigated algorithms when the statistical errors on the measurements become large.