Covariance matrix estimation for the STAP based on the Bayes criterion
Guisheng Liao · Journal of Xidian University · 2008
For the environment in which the clutter power changes slowly with distance,a novel weighting maximum likelihood estimation(WMLE) algorithm is proposed that uses the Bayes criterion to improve the approximative covariance matrix estimation for Space-Time Adaptive Processing(STAP).By the event definition and the Bayes criterion,the precise computing method for the weight coefficient is given,this method also gives the efficient solution to finding the weight coefficient for WMLE.Simulation attests its correctness and effectiveness.