钱扬, 耿军平, 梁仙灵, 朱卫仁, 姚羽, 彭政, 金荣洪. 基于Bessel权向量的宽带波束形成器[J]. 电波科学学报, 2016, 31(6): 1093-1098. doi: 10.13443/j.cjors.2016102101
      引用本文: 钱扬, 耿军平, 梁仙灵, 朱卫仁, 姚羽, 彭政, 金荣洪. 基于Bessel权向量的宽带波束形成器[J]. 电波科学学报, 2016, 31(6): 1093-1098. doi: 10.13443/j.cjors.2016102101
      QIAN Yang, GENG Junping, LIANG Xianling, ZHU Weiren, YAO Yu, PENG Zheng, JIN Ronghong. Algorithm of broadband beamformer based on Bessel function[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2016, 31(6): 1093-1098. doi: 10.13443/j.cjors.2016102101
      Citation: QIAN Yang, GENG Junping, LIANG Xianling, ZHU Weiren, YAO Yu, PENG Zheng, JIN Ronghong. Algorithm of broadband beamformer based on Bessel function[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2016, 31(6): 1093-1098. doi: 10.13443/j.cjors.2016102101

      基于Bessel权向量的宽带波束形成器

      Algorithm of broadband beamformer based on Bessel function

      • 摘要: 针对均匀线阵接收宽带信号产生的方向图畸变问题, 提出了一种基于Bessel权向量的宽带波束形成器.从截断后的Bessel级数展开式与均匀线阵的方向图函数相似的特性出发, 推导Bessel级数的截断位置与阵列单元数的关系, 并确定使用第一类Bessel函数设计均匀线阵的权向量.仿真结果表明:应用Bessel权向量后, 在1~3 GHz频率范围内, 均匀线阵可以无失真地接收宽带信号, 不同频率的方向图函数幅值与期望方向图函数幅值的相对误差降低到10-3以下, 且单元越多相对误差越小.与现有方法相比, 本方法直接利用截断后的Bessel级数展开式系数设计权向量, 计算简单且精度高.

         

        Abstract: We present a novel broadband beamformer using a Bessel function based weight vector, aiming at solving the pattern distortion of wideband signals received by a uniform linear array.Owing to the similarity of the Bessel series and the pattern function of the uniform linear array, we design an weight vector based on Bessel functions of the first kind by deducing the relationship between the truncated position of Bessel series and the number of array elements.Simulation results show that the uniform linear array with a proper weight vector can receive wideband signal from 1 to 3 GHz with negligible distortions.The relative amplitude error for pattern functions at different frequencies remains below 10-3, and it can be further reduced by increasing the number of the array elements.In comparison with the existing methods, our proposed broadband beamformer directly uses the coefficients of the truncated Bessel series expansions as the weight vector, possesses high precision, and reduces the computational complexity significantly.

         

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