Positioning for NLOS Propagation: Algorithm Derivations and Cramer-Rao Bounds

Mobile positioning has drawn significant attention in recent years. In dealing with the non-line-of-sight (NLOS) propagation error, the dominant error source in the mobile positioning, most previous research in this area has focused on the NLOS identification and mitigation. In this paper, we investigate new positioning algorithms to take advantage of the NLOS propagation paths rather than cancelling them. Based on the prior information about the NLOS path, a least squares based position estimation algorithm is developed and its performance in terms of root mean square error (RMSE) is also analyzed. Furthermore, the maximum likelihood based algorithm is presented to jointly estimate the mobile´s and scatterers´ positions. The Cramer-Rao lower bound on the RMSE is derived for the benchmark of the performance comparison. Finally, the performances of the proposed algorithms are evaluated analytically and via computer simulations. Numerical results demonstrate that the simulated results closely match the derived analytical results