Quickest detection of statistical changes with application to tracking

As part of the track-management process it is necessary to know when new tracks start and when old ones die. Thus some knowledge of the theory of detection of statistical changes is important, and the purpose of this talk is to give the audience some overview of what is available. Specifically, we shall discuss sequential testing, this information necessary as a precursor to an understanding of the procedure and performance of the Page "quickest" detection of statistical changes. We shall also discuss the Shiryaev test, which represents a more Bayesian point of view. We shall present applications to detection of target spawn based on monopulse radar data, and also to the track management of sonar targets whose aspect-dependent SNR is modeled as hidden Markov - the suboptimality of Page procedures for detection of a changes between HMMs is rather surprising.