MULTISOURCE DELAY ESTIMATION - NONSTATIONARY SIGNALS

This paper studies delay estimation in a very general framework: multiple sources, correlated noises, nonstationary random signals, and varying delays. We derive the optimal maximum likelihood (ML) delay estimator, analyze its performance via the Cramer-Rao inequality, and test by experimentation with synthetic data. The present time-varying delay estimator extends to the nonstationary/multisource environment the estimators of Ng and Bar-Shalom, Kirlin and Dewey, and Knapp and Carter. However, as it will be apparent, our receiver significantly departs from the correlator structures of these authors.