Ambiguity function and Cramer-Rao bound in the multisignal case

The author aims to bridge the gap between the classical theory of signal processing and modern signal processing for multiple signals. The classical ambiguity function of a single signal used in signal detection and estimation has been extended to superimposed multiple signals. It is shown that the geometric curvature of the generalised ambiguity function at its peak determines the Cramer-Rao bound for estimating unknown 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