CRLB and ML for parametric estimate: New results

In the present paper, we calculate the Cramer-Rao Lower Bound (CRLB) for the Pd 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 = 1 and Pfa = 0. The results obtained by means of a Monte Carlo simulation successfully validate our extended enhanced estimation method.

[1]  Branko Ristic,et al.  Cramer-Rao bound for nonlinear filtering with Pd<1 and its application to target tracking , 2002, IEEE Trans. Signal Process..

[2]  Alfonso Farina,et al.  Target tracking with bearings - Only measurements , 1999, Signal Process..

[3]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[4]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[5]  Y. Bar-Shalom,et al.  Low observable target motion analysis using amplitude information , 1995 .

[6]  N. Gordon,et al.  Cramer-Rao bounds for non-linear filtering with measurement origin uncertainty , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[7]  Branko Ristic,et al.  A comparison of two Crame/spl acute/r-Rao bounds for nonlinear filtering with P/sub d/<1 , 2004, IEEE Transactions on Signal Processing.

[8]  A. Farina,et al.  Estimation accuracy of a landing point of a ballistic target , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).

[9]  Yaakov Bar-Shalom,et al.  Track formation with bearing and frequency measurements in clutter , 1990 .