Using Memetic Algorithm to optimize location estimate of mobile station in non-line-of-sight environment

Wireless location technology is mainly used to estimate the location of mobile station (MS). Positioning accuracy of the mobile station completely depends on the propagation environment of the wireless communications. The error caused by non-line-of-sight (NLOS) is the most urgent problem in positioning research. Memetic Algorithm (MA), similar to Genetic Algorithm (GA), is also called Genetic Algorithm combined with local search. MA is based on the concept of cultural evolution that combines with multi-point search features to solve combinatorial optimization problems. In this paper, we propose a novel location scheme by using MA that employs time of arrival (TOA) measurements from three base stations (BSs) to estimate the location of MS. MA is utilized to find the optimum solution in the intersections of three TOA circles. The optimum solution can be regarded as the MS location where minimizes the three circular intersection region caused by NLOS error. Simulation result will show that the proposed position location method improves the performance by mitigating the NLOS ranging error.