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波束空间法是阵列自适应处理的一种重要的降维方法,可使运算量大大降低;而特征空间法只需较少的数据采样数就可以加速波束形成的收敛。将波束空间处理与特征空间处理结合起来,给出了基于特征空间的波束域自适应波束形成算法。新算法降低了自适应处理中对数据采样数的要求,并且具有更好的信噪比特性和稳健性。仿真结果证明了算法的优越性。
Beam space method is an important dimension reduction method for array adaptive processing, which can greatly reduce the computational complexity. However, the eigenspace method can speed up the beamforming convergence with fewer data samples. Combining beam space processing and feature space processing, a beamforming adaptive beamforming algorithm based on feature space is proposed. The new algorithm reduces the number of data samples required for adaptive processing and has better signal-to-noise characteristics and robustness. Simulation results show the superiority of the algorithm.