Title :
CFAR data fusion using fuzzy integration
Author :
Leung, S.W. ; Minett, James W.
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, Hong Kong
Abstract :
This paper presents a new approach to constant false alarm rate (CFAR) data fusion using fuzzy integration. The paper describes how any CFAR scheme may be implemented as part of a fuzzy data fusion scheme by choosing an appropriate membership function to represent the CFAR threshold. Once the threshold membership function of the fuzzy integrator has been set up, the false alarm rate of the scheme is independent of fluctuations in interference mean power and depends only on the number of signals integrated by the data fusion unit and the required false alarm rate
Keywords :
fuzzy set theory; integration; interference (signal); sensor fusion; signal detection; constant false alarm rate; fuzzy data fusion; fuzzy integration; interference mean power; signal detection; threshold membership function; Data engineering; Detectors; Fluctuations; Fuzzy sets; Interference; Logic; Random processes; Signal detection; Signal processing; Signal processing algorithms;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.552363
