AMBIGUITY FUNCTION AND CRAMER-RAO BOUND IN THE MULTISIGNAL CASE

The author aims to bridge the gap between the classical theory of sign al processing and modern signal processing for multiple signals. The c lassical ambiguity function of a single signal used in signal detectio n and estimation has been extended to superimposed multiple signals. I t is shown that the geometric curvature of the generalised ambiguity f unction at its peak determines the Cramer-Rao bound for estimating unk nown parameters in multiple signals and that the asymptotic covariance matrix of the maximum likelihood estimates of the unknown parameters is also given by the curvature when all signals are strong.