现有研究表明,有效利用先验知识可以较好地解决机载雷达自适应信号处理中的非均匀杂波问题.分析了当前知识辅助机载雷达杂波抑制方法研究的基本情况,从外信息源数据与雷达观测数据的关联、智能样本选取与滤波器选择两个方面分析了间接利用先验知识方法的研究进展,从先验协方差估计、预白化类空时自适应处理(STAP)算法以及贝叶斯滤波STAP算法三个方面分析了直接利用先验知识的方法的研究进展,分析了基于先验知识的CFAR处理方法以及高逼真度杂波建模与仿真的研究进展.建立在对现有研究分析的基础上,从对更多信息源的使用和更有效融合先验知识的STAP方法两个方面提出了一些值得进一步深入研究的问题.%A confluence of existing researches have shown that using priori knowledge can efficiently mitigate the heterogeneous clutter of airborne/space-based radar. A brief overview of significant progress in knowledge-aided (KA) methods for airborne radar clutter suppression is presented. The recent advances of clutter mitigation methods exploiting a prior knowledge in indirect way,such as associating radar data with dissimilar data, intelligent training and filter selecting, are introduced. Especially, some methods for registration of radar data and other resources data are elaborated. The progress in Bayesian filtering and data pre-whitening which can directly filter the incoming multi-dimensional data stream are analyzed, including the priori covariance matrix estimation, pre-whitened STAP filtering and Bayesian STAP filtering. Furthermore, a brief overview of the KA CFAR algorithms, high-fidelity clutter modeling and validation data of KA-based airborne radar adaptive processing algorithms are conducted. Although great progress has been made in clutter mitigation methods using KA, there are some unsolved problems in the real application. For these problems, we give some idea about using multiple data sources and effectively exploiting prior knowledge.
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