The use of fuzzy spaces in signal detection

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)175-184
Journal / PublicationFuzzy Sets and Systems
Volume114
Issue number2
Publication statusPublished - 1 Sep 2000

Abstract

The fuzzy constant false alarm rate (CFAR) detector, which is based on the M-out-of-N binary detector, is characterized and compared with the optimal Neyman-Pearson detector. It replaces the crisp M-out-of-N binary threshold with a soft, continuous threshold, implemented as a membership function. This function is chosen so that the output is equal to the false alarm rate of the binary detector, and therefore maps the observation set to a false alarm space corresponding to the false alarm rate, PFA. An analogous membership function is also developed mapping observations to a detection space which corresponds to the detection rate, PD. These two spaces allow different detectors to be compared directly with respect to the two important detection performance indices, PFA and PD. Comparison of the false alarm space and detection space indicates that the fuzzy CFAR detector and Neyman-Pearson detector detect signals in a different manner and have different detection properties. Nevertheless, performance results illustrate that the fuzzy CFAR detector achieves detection performance comparable to the optimal Neyman-Pearson detector. © 2000 Elsevier Science B.V.

Research Area(s)

  • Decision making, Signal detection

Citation Format(s)

The use of fuzzy spaces in signal detection. / Leung, S. W.; Minett, James W.

In: Fuzzy Sets and Systems, Vol. 114, No. 2, 01.09.2000, p. 175-184.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review