A DATA-SELECTIVE LS SOLUTION TO TDOA-BASED SOURCE LOCALIZATION

This data-set was used for the localization of an emitter based on Time Difference of Arrival (TDoA). 

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. 

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.

Considering all TDoA values can eventually degrade the accuracy of the localization method due to the presence of heavily noisy measurements. 

The ICASSP 2019 paper entitled " A DATA-SELECTIVE LS SOLUTION TO TDOA-BASED SOURCE LOCALIZATION", by employing a data-selective approach, proposes a closed-form LS solution that disregards bad measurements. 

To this end, two distinct objective functions are used: one to obtain a solution and a second one to test that particular solution among all possible ones within a subset of measurements. 

This data-set corresponds to all recordings of the real-life experiment carried out in this paper. From processing these recordings, we observe the superior performance of the proposed algorithm in the source localization problem.