CRLB and ML for parametric estimate: New results

In the present paper, we calculate the Cramér–Rao Lower Bound (CRLB) for the Pd<1Pd<1 and Pfa>0Pfa>0 case, accounting both for missed detections and false alarms, for an estimation problem in a surveillance system where the measurements are acquired by a radar. The analysis, which is limited to the parameter estimation for a deterministic steady-state target motion, is a further innovation in the computation of the CRLB of maximum likelihood estimators for deterministic steady-state models; in fact, the classical theory applies only in the unrealistic case of Pd=1Pd=1 and Pfa=0Pfa=0. The results obtained by means of a Monte Carlo simulation successfully validate our extended enhanced estimation method.