Estimation of closely-spaced paths via particle filters for WCDMA positioning

Multipath delay estimation is an important and challenging issue for any mobile communication system. Severe transmission conditions in fast changing environment, such as strong interference, shadowing or closely spaced multipaths may affect the capability of estimating correctly the channel parameters. In mobile positioning, accurate estimates of line-of-sight delay with a resolution less than one chip are needed to locate correctly the mobile receiver. Another challenging issue in multipath delay estimation in CDMA networks is the nonlinear dependency of the channel with respect to the multipath delays. In this paper, we introduce a particle-based sequential Monte Carlo filter for joint estimation of channel coefficients and delays in multiuser closely spaced paths WCDMA environment. The simulation results show that the proposed algorithm is stable, fast converging, and outperforms the classic extended Kalman filter-based approach.