THE DETECTION OF MULTIPLE UNKNOWN SIGNALS BY ADAPTIVE FILTERS
JOHNS HOPKINS UNIV BALTIMORE MD CARLYLE BARTON LAB
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Filters which modify their structures in order to recognize initially unknown waveforms in Gaussian noise are investigated experimentally. The class of filters discussed include two types previously described n the literature and one new type designed explicitly for operating in a mutiple waveform environment. The new structure processes the data in a nonlinear fashion and effectively sets upa narrow decision region about the estimate of the waveform. The parallel operation of adaptive systems for detecting and estimating the signal parameters of multiple signals simultaneously is also discussed. The results clearly demonstrate the possibility of using filters of the new type for automatic data processing. Results are given in the form of learning curves which show the effects of correct and incorrect decisions. Included in much of the discussion is a graphical interpretation of the filtering process. Two unusual applications of the new filter structure are discussed.
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