A Improved Chan Algorithm Basing on Particle Filtering in NLOS Environment
In the wireless positioning issue basing on TOA/TDOA, NLOS makes a great impact on the positioning accuracy. This paper presents a particle filtering based improved Chan Algorithm. Considering the case of multiple base stations, in the first step we use Chan algorithm to get the initial location estimation basing on the information provided by the base stations which are divided into subgroups. In the second step, we calculate the contributions of these estimated locations, and then use these contributions in the particle filtering framework to get the MAP of the location. Experimental results show that the improved algorithm can suppress the effect of the NLOS and can get better location estimation than the basic algorithm.
Z. Q. Wang et al., "A Improved Chan Algorithm Basing on Particle Filtering in NLOS Environment", Advanced Materials Research, Vols. 217-218, pp. 1564-1568, 2011