Optimal semi-adaptive search with false targets
McCray, John P.
Royset, Johannes O.
Singham, Dashi I.
MetadataShow full item record
Searchers frequently encounter the presence of false targets or clutter, which appears indistinguishable from the real target and must be identified in a second stage of the search. False targets can significantly impede search operations, such as underwater recovery and mine warfare, when contact investigation is costly. Current literature optimizes these searches by applying Bayesian updates to the prior distributions for the real and false targets, in what is called a semi-adaptive search. We take full advantage of intermediate search results, along with soft information about the target, to build up-to-date maximum likelihood estimates of the location of the real target and the distribution of the clutter. Using these estimates in place of the priors, we update and improve the allocation of search effort as the operation progresses. In a detailed simulation study, this new approach increases the probability of finding the target by up to 12% over the optimal semi-adaptive plan without such estimates. These gains are robust to variation in the false target density, time to identify false targets, and total search time available.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Showing items related by title, author, creator and subject.
Hasting, Matthew D. (Monterey, California. Naval Postgraduate School, 2009-06);This thesis investigates the visual search process and the effect of contextual information on the search process in an urban combat environment. High resolution combat simulation models implement a parallel sweeping or ...
Recalde, Cesar Julio (Monterey, California. Naval Postgraduate School, 1996-09);This thesis develops, implements and tests a Tactical Decision Aid for a Reactive Target ASW Active Search. The mode! uses a Bayesian Filtering Process to fuse information from a real world search conducted by several ...
Chung, Timothy H.; Silvestrini, Rachel T. (2014);This article explores a probabilistic formulation for exhaustive search of a bounded area by a single searcher for a single static target. The searcher maintains an aggregate belief of the target’s presence or absence in ...