A non-line-of-sight mitigation technique based on ML-detection

Geolocation in non line of sight (NLOS) environments is an important issue in wireless communication networks. In several recent publications related with the nature and magnitude of the NLOS phenomenon it is concluded that this is the major source of error in position estimators based on time measurements. This article presents a new approach to ameliorate the effect of the NLOS exploiting the redundant time measurements in scenarios with more than the minimum number of base stations (BS). This redundant data allows to formulate the problem as a test of hypothesis performing a hard decision to discard the BS considered to be in a NLOS scenario. Numerical simulations show that the proposed algorithm can discard the NLOS errors in certain scenarios. The algorithm is also compared with some other existing methods to show the advantage of the new approach.