TOA localization using RSS weight with path loss exponents estimation in NLOS environments

This paper proposes a localization algorithm that needs no priori knowledge about path loss exponents for non-line-of sight (NLOS) environments. The proposed algorithm utilizes both time-of-arrival (TOA) measurements and received-signal-strength (RSS) measurements. In the proposed localization algorithm the distances estimated with TOA measurements are weighted by the believable factor (BF) derived from the difference between the estimated distance with TOA measurements and that with RSS ones. In addition the path loss exponents are estimated for each node in a maximum likelihood (ML) manner. Simulation results show that the proposed algorithm can efficiently reduce the effect of NLOS error and achieve higher localization accuracy than the other conventional algorithms, TOA, RSS, and BF ones, without priori knowledge about the path loss exponents.