Novel method for CFAR data fusion

Weixian Liu*, Yilong Lu, Jeffrey S. Fu

*Corresponding author for this work

Research output: Contribution to conferenceConference Paperpeer-review

4 Scopus citations


Detection system with distributed sensors and data fusion are increasingly being used by surveillance system. There has been a great deal of theoretical study into decentralized detection networks composed of similar, independent sensors. To solve the resulting nonlinear system, exhaustive search and some approximation methods are adopted, however, those often cause either the system insensitive to some parameters or lead to the suboptimal results. In this paper, the genetic algorithm is investigated to obtain the optimal results on constant false alarm rate data fusion.

Original languageEnglish
Number of pages10
StatePublished - 2000
Externally publishedYes
Event10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000) - Sydney, Australia
Duration: 11 12 200013 12 2000


Conference10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000)
CitySydney, Australia


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