Novel TOA location algorithms based on MLE and MMSEE for NLOS environments

Wireless positioning has now gained considerable attention due to its wide applications in military, environmental, health and commercial systems. One of the main problems facing accurate positioning in actual wireless positioning system is non-line-of-sight (NLOS) propagation where the signal arrives at a base station from reflections. Although maximum likelihood estimator (MLE) and minimum mean square error estimator (MMSEE) have been successfully applied in time-difference-of-arrival (TDOA) based localization methods for LOS environments, the problem of mobile location for time-of-arrival (TOA) positioning technique is still an open issue. Moreover, the performance of MLE and MMSEE may be sharply degraded in a real wireless channel due to the large errors of range measurements caused by NLOS propagation. In this paper, effective location algorithms based on NLOS weighting are proposed to mitigate NLOS errors. Main contributions of this paper are listed as follows: (1) both MLE and MMSEE are extended from TDOA to TOA; (2) weight matrix of the proposed method considers the effects of NLOS errors such that NLOS errors can be effectively suppressed. The simulation results show that the proposed method has better positioning accuracy than existing methods.