A Data-selective LS Solution to TDOA-based Source Localization

In this paper, the localization of an emitter based on Time Difference of Arrival (TDoA) has been investigated. The classical least-squares (LS) algorithm, with a limited number of TDoA measurements, has been utilized for obtaining a closed-form solution to the source localization problem. Recently, an extension of the classical LS algorithm has been employed in an attempt to improve the precision of the localization technique by using a larger set of TDoA estimates. However, considering all TDoA values can eventually degrade the accuracy of the localization method due to the presence of heavily noisy measurements. In this work, by employing a data-selective approach, we have proposed a closed-form LS solution that disregards bad measurements. To this end, we have used two distinct objective functions, one to obtain a solution and a second one to test that particular solution among all possible ones within a subset of measurements. Simulation results indicate the superior performance of the proposed algorithm in the source localization problem.