针对杂波功率随距离缓变的非均匀环境,提出了一种新的基于Bayes准则的加权最大似然估计(WMLE)算法,以改善空时自适应处理(STAP)中的协方差矩阵估计.通过对训练数据进行事件定义,利用Bayes准则给出了加权系数的准确计算方法,解决了WMLE中加权系数的求解难题.仿真分析验证了所提出算法的正确性和有效性.
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.