Generalised Decentralised Fuzzy CA-CFAR Detector in Pearson distributed Clutter
In this paper, we analyze the decentralized CA-CFAR detector using fuzzy fusion rules in heavy tailed clutter modeled by a Pearson distribution. We generalize our study by considering a distributed detection system with “L detectors and using the “Maximum, “Minimum, “Algebraic sum and “Algebraic product fuzzy rules at the data fusion centre. We derive the membership function which maps the decision to the false alarm space and compute the threshold at the fusion centre. From the Monte-Carlo simulations conducted to assess the detection performance in homogeneous Pearson distributed clutter, we observe that the probability of detection increases with the number of detectors. However, there a maximum number of detectors (L=11) above which no improvement is obtained.
CFAR detecor data fusion fuzzy Pearson clutter
Hilal Abdenour Meziani Faouzi Soltani
Laboratoire “ Signaux et Systèmes de Communication “Département d’électronique, Université de Constantine Constantine, Algeria
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
1915-1917
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）