Accession Number : ADA264100


Title :   Enhanced Convergence Adaptive Detection


Descriptive Note : Final rept. 1 Feb-30 Nov 1991


Corporate Author : CORNELL UNIV ITHACA NY DEPT OF ELECTRICAL ENGINEERING


Personal Author(s) : Steinhardt, Allan O


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a264100.pdf


Report Date : 28 Feb 1993


Pagination or Media Count : 8


Abstract : We addressed the problem of detecting targets using an array of active sensors. We have been concerned with devising means of obtaining reliable detection with a small number of samples (small relative to the number of unknown parameters). This problem arises with large arrays, and/or low cross section targets. Past techniques for addressing this problem incorporated prior structure into likelihood procedures. Such approaches are (1) intractable, requiring iterative solution, (2) not CFAR, and (3) not optimal. We have approached this problem using group symmetries. Specifically, we introduce a framework for exploring array detection problems in a reduced dimensional space by exploiting the theory of invariance in hypothesis testing. This involves calculating a low dimensional basis set of functions called the maximal invariant, the statistics of which are often tractable to obtain, thereby making analysis feasible and facilitating the search for tests with some optimality property. Using this approach, we obtain a locally most powerful test for the unstructured covariance case and show that the Kelly and AMF detectors form an algebraic span for any invariant detector. Applying the same framework to structured covariance matrices, we gain some insights and propose several new detectors which are shown to outperform existing detectors.


Descriptors :   *TARGET DETECTION , MATCHED FILTERS , DETECTION , DETECTORS , GAUSSIAN NOISE , ARRAYS , TARGETS , CROSS SECTIONS , ADAPTIVE SYSTEMS , CONVERGENCE , ADAPTIVE FILTERS , COVARIANCE , INVARIANCE , TEST AND EVALUATION , SIGNAL PROCESSING


Subject Categories : Miscellaneous Detection and Detectors


Distribution Statement : APPROVED FOR PUBLIC RELEASE