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Sequential Detection of a Weak Target in a Hostile Ocean Environment.

DE2006862377

Publication Date	2005
Personal Author	Candy, J. V.; Sullivan, E. J.
Page Count	12
Abstract	When the underlying physical phenomenology (medium, sediment, bottom, etc.) is space-time varying along with corresponding nonstationary statistics characterizing noise and uncertainties, then sequential methods must be applied to capture the underlying processes. Sequential detection and estimation techniques offer distinct advantages over batch methods. A reasonable signal processing approach to solve this class of problem is to employ adaptive or parametrically adaptive signal models and noise to capture these phenomena. In this paper, we develop a sequential approach to solve the signal detection problem in a nonstationary environment.
Keywords	Target detection Ocean environments Detection Targets Signal processing Signal enhancement Sequential detection theory Model-based processor
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Lawrence Livermore National Lab., CA.; Department of Energy, Washington, DC.
Supplemental Notes	Sponsored by Department of Energy, Washington, DC.
Document Type	Technical Report
NTIS Issue Number	200618

Sequential Detection of a Weak Target in a Hostile Ocean Environment.

Sequential Detection of a Weak Target in a Hostile Ocean Environment.
DE2006862377

Publication Date	2005
Personal Author	Candy, J. V.; Sullivan, E. J.
Page Count	12
Abstract	When the underlying physical phenomenology (medium, sediment, bottom, etc.) is space-time varying along with corresponding nonstationary statistics characterizing noise and uncertainties, then sequential methods must be applied to capture the underlying processes. Sequential detection and estimation techniques offer distinct advantages over batch methods. A reasonable signal processing approach to solve this class of problem is to employ adaptive or parametrically adaptive signal models and noise to capture these phenomena. In this paper, we develop a sequential approach to solve the signal detection problem in a nonstationary environment.
Keywords	Target detection Ocean environments Detection Targets Signal processing Signal enhancement Sequential detection theory Model-based processor
Source Agency	Technical Information Center Oak Ridge Tennessee
Corporate Authors	Lawrence Livermore National Lab., CA.; Department of Energy, Washington, DC.
Supplemental Notes	Sponsored by Department of Energy, Washington, DC.
Document Type	Technical Report
NTIS Issue Number	200618