双面声阵列波束形成的正则化改进算法
Improved regularization algorithm of double layer antenna beamforming
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摘要: 双面声阵列波束形成能够区分识别位于不同扫描平面的相干声源,然而该算法在低信噪比条件下识别精度较低。针对此问题提出一种迭代正则化改进算法,通过迭代方法更新正则化矩阵与波束形成输出,在不断提升正则化稳定性、抑制干扰旁瓣的基础上使声学云图主瓣向实际相干声源点处聚焦。数值仿真与实验算例结果显示,改进算法在中高频代表频率下能够正确区分相干声源前后方位,并具有相对原算法更高的识别精度。从而表明:从反问题正则化角度对原算法进行优化改进是理论可行的;正则化矩阵的具体形式与广义逆波束形成输出的空间分辨率紧密相关,且可通过迭代方法将二者整合以提高声源识别精度。Abstract: Double-layer-antenna beamforming can distinguish coherent sound sources at different parallel scan plane.However,its identification accuracy is unsatisfactory under low signal-to-noise ratio.To solve this problem,a modified algorithm is proposed:iterative regularization is used to update the regularization matrix and beamforming output.Thus,the side lobes are suppressed for the enhanced stability and the main lobe is sharpened to the real source point.Simulation and experiment results show that the proposed algorithm can locate the front and rear coherent sources with high accuracy.Therefore,modifying the original algorithm form the perspective of inverse problem is theoretically feasible.And the content of regularization matrix has tight relation with the spatial resolution of generalized inverse beamforming.These two factors can be integrated to improve the identification accuracy by iteration method.