Convergence performance of adaptive detectors, part 1
Abstract
Convergence results for a mean level adaptive detector (MLAD) are presented. The MLAD consists of an adaptive matched filter (for spatially correlated inputs) followed by a mean level detector (MLD). The optimal weights of the adaptive matched filter are estimated from one batch of ata and applied to a statistically independent batch of nonconcurrent data. The threshold of the MLD is determined from the resultant data. Thereafter, a candidate cell is compared against this threshold. Probabilities of false alarm and detection are derived as functions of the threshold factor, the order of the matched filter, the number of independent samples per channel used to calculate the adaptive matched filter weights, the number of samples used to set the MLD threshold, and the output signaltonoise power ratio of the optimal matched filter. A number of performance curves are shown and discussed.
 Publication:

Naval Research Lab. Report
 Pub Date:
 July 1991
 Bibcode:
 1991nrl..reptS....G
 Keywords:

 Adaptive Filters;
 Convergence;
 Detectors;
 Matched Filters;
 Probability Theory;
 Signal To Noise Ratios;
 Estimating;
 False Alarms;
 Electronics and Electrical Engineering