空域数据重排的后多普勒自适应处理方法

doi:10.7527/S1000-6893.2015.0002

Abstract

Abstract:

The traditional post-Doppler adaptive beam-forming approaches such as factored approach (FA) and extended factored approach (EFA) can significantly reduce the computation-complexity and training sample requirement in adaptive processing. However, their clutter suppression and moving target detection ability can be notably degraded with the increasing number of antenna elements since the homogeneous training samples in real clutter environment are always limited. Aimed at this problem, the post-Doppler adaptive processing method based on the spatial data rearrangement is proposed. This method rearranges the spatial data vector, after being filtered by Doppler, into a matrix that has close columns and rows. The spatial weights are also re-expressed as a separation form. Then a bi-quadratic cost function is obtained. The cyclic iteration is applied to solving the desired weight vector. Experimental results show that the proposed method has the advantages of fast convergence and small training sample requirement. It also has greater clutter suppression ability especially in large antenna array elements compared to FA and EFA.

Key words: space-time adaptive processing (STAP), clutter suppression, convergence, dimension reduction, cyclic iteration

CLC Number:

V243.2

ZHOU Yan, FENG Dazheng, ZHU Guohui. Post-Doppler adaptive processing method based on spatial data rearrangement[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(9): 3020-3026.

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Post-Doppler adaptive processing method based on spatial data rearrangement

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