Delay Estimation with Nonstationary Signals and Correlated Observation Noises

The problem of delay estimation is considered. The approach taken generally considers nonstationary signals and correlated measurement noises. The signals are described as the output of a finite dimensional linear system driven by white noise. The estimator is conceptually equivalent to two blocks. The first has the structure of a Kalman-Bucy filter for signals with delays [9]. The second minimizes the log-likelihood function. When stationary, long observation interval (SLOT) [7] assumptions are considered, the cross-correlator array receiver [1] is recovered. The results of the paper are then a generalization of the classical solution.