Time delay estimation for spread spectrum signals using generalized cross correlation

The generalized cross correlation approach to time delay estimation is tested with direct sequence and frequency hopping spread spectrum signals in white and narrowband noise. The performance of six correlation filters [1] are evaluted via Monte Carlo simulation where sample variances and mean-square errors (MSE) are estimated for several signal-to-noise ratios. The results allow one to choose an optimal filter according to a minimum mean square error criterion. Additionally, the sample variances are compared to the lower bound developed in [2].