CFAR data fusion of multistatic radar system under homogeneous and nonhomogeneous backgrounds

Multistatic Radar with distributed sensors and data fusion are increasingly being used by surveillance system. The performance of that detection system mainly depends on the data fusion process. There has been a great deal of theoretical study on decentralized detection networks in homogeneous and nonhomogeneous backgrounds. To solve the resulting nonlinear system, exhaustive search and some crude approximations are adopted, however, those often cause either the system insensitive to some parameters or the suboptimal results. In this paper, a novel flexible genetic algorithm is investigated to obtain the optimal results on constant false alarm rate data fusion. Using this approach, all system parameters are directly coded in decimal chromosomes and they can be optimized simultaneously. Furthermore, our method can also be implemented for the more general situations.