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针对部分相关、中等起伏目标的最佳检测，本文提出了基于快速子空间分解的组滤波自适应杂波抑制算法．由于采用了快速子空间分解方法，明显降低了算法运算量而使其易于实时实现．文中所采用的最小二乘同组滤波相结合的方法使得即使在非平稳的条件下也可以获得良好的杂波谱估计，进而可以有针对性地完成特定多普勒域的目标提取，实现在变化杂波条件下的有效杂波抑制和目标检测．
Aiming at the best detection of some related and medium fluctuation targets, this paper proposes a group filtering adaptive clutter suppression algorithm based on fast subspace decomposition. Due to the adoption of a fast subspace decomposition method, the computational complexity of the algorithm is significantly reduced, making it easy to implement in real time. In this paper, the combination of least-squares filter with the same set of methods makes it possible to obtain good clutter spectrum estimation even under non-stationary conditions, and then can be targeted to complete the extraction of the target of a particular Doppler domain to achieve the change Effective Clutter Suppression and Target Detection under Clutter Conditions.