Improved positioning algorithm based on two step least square in NLOS environments

Non-line-of-sight （NLOS） propagation is a major source of error for accurate time-of-arrival （TOA） location estimation. The two-step least square （LS） method, which does not need any information about the distribution of the NLOS error, has been studied in related researches to provide efficient location estimation of the mobile terminal （MT）. By observing the estimation of the error covariance matrix in the two-step LS method, this paper finds that the measured distances are more suitable than the initial estimated distances by maximum likelihood （ML） algorithm in NLOS environments. Moreover, by making use of the geometry relations among fixed terminals （FTs）, some measured distances which are corrupted by big NLOS errors may be reduced. Further, an iteration method can be adopted to further improve the performance of the algorithm. Accordingly, an improved algorithm based on the two-step LS method is proposed. Simulation results demonstrate that the improved algorithm has better performance than the two-step LS method and converges more quickly. Meanwhile, it is robust in different NLOS environments.