On M-ary Sequential Hypotheses Testing for the Classification of Radar Signals.
OHIO STATE UNIV COLUMBUS ELECTROSCIENCE LAB
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This report is concerned with the performance of M-ary sequential hypothesis tests applied to the classification of radar signals. In the first part of this report, several available M-ary sequential algorithms are considered. These include the algorithms due to Reed, Armitage and Palmer. Modifications of the existing algorithm are considered and their effects on the average number of required measurements and the resulting error performance are examined. Three other techniques are also proposed, a tree algorithm and a sequential maximum a posteriori test as well as a sequential version of the various algorithms by means of Monte-Carlo simulations of the radar signal observations. The performance of these techniques is compared and the relative merits of each algorithm are discussed.
- Active and Passive Radar Detection and Equipment