The use of fuzzy spaces in signal detection

✍ Scribed by S.W. Leung; James W. Minett

• Publisher: Elsevier Science
• Year: 2000
• Tongue: English
• Weight: 391 KB
• Volume: 114
• Category: Article
• ISSN: 0165-0114
• DOI: 10.1016/s0165-0114(98)00268-1

✦ Synopsis

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 di erent 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 di erent manner and have di erent detection properties. Nevertheless, performance results illustrate that the fuzzy CFAR detector achieves detection performance comparable to the optimal Neyman-Pearson detector.