The joint estimation of linear and nonlinear state variables remains challenging, especially in multiuser communications applications where the state dimension is large and signal to noise ratio is low. In this paper, an efficient Particle Filter (PF) is developed to make estimates of nonlinear time delay parameters in the presence of non-Gaussian noise. The PF method has the advantage that the importance weights are easily evaluated and the importance density can be easily sampled. We propose a PF-based algorithm with Resampling schemes for the estimation of closely-spaced path delays and related coefficients in CDMA environments. Furthermore we present a number of resampling schemes, namely: Multinomial Resampling (MR), Residual Resampling (RR) and Minimum Variance Resamplings (MVR). The simulation results show that MR scheme outperforms the other selection schemes. We also show that it provides a more suitable method for tracking time-varying amplitudes and delays in CDMA communication systems than RR and MVR schemes.
展开▼
