Improved adaptive clutter suppression based on multi-look processing in heterogeneous background

It is known that the performance of adaptive clutter suppression may be reduced seriously in a heterogeneous background, due to the lack of enough training samples to exactly obtain the optimum weight. Furthermore, a background will be further heterogeneous with the improving of range resolution. In this paper, we propose an improved adaptive clutter suppression method based on multi-look processing, which can mitigate background homogeneity by reducing the range resolution. Furthermore, non-coherent integration is applied among multiple sub-looks to improve the clutter suppression performance. Finally, some results of real measured data are provided to demonstrate the effectiveness of the method in a heterogeneous background.

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