一个基于空间源连贯性的自适应循环增益CLEAN算法,用于端/右歧视
Songyue Qu1,2, Lianghao Guo1
1State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, People's Republic of China.
本研究引入了一个自适应的CLEAN算法 (A-CLEAN-SC),以改善在抵达估计方向上的港/右歧视. 该方法增强了通过干扰工件掩盖的弱目标的检测.
科学领域:
- 信号处理 信号处理
- 阵列信号处理 阵列信号处理
- 电磁学 电磁学 电磁学 电磁学
背景情况:
- 近线性数组对于到达方向 (DOA) 估计至关重要.
- 阵列中的圆柱体对称性对/右歧视 (PSD) 提出了挑战.
- 干扰诱导的镜像工件可以掩盖弱点目标.
研究的目的:
- 用近线性数组来解决DOA估计中的港/右歧视 (PSD) 问题.
- 开发一种方法来检测被干扰诱导的镜像工件所掩盖的弱目标.
- 为了改善镜子抑制和弱目标检测能力之间的权衡.
主要方法:
- 引入基于空间源连贯性的自适应循环增益CLEAN算法 (A-CLEAN-SC).
- 作为循环增益函数的检测和错误报警概率的制定.
- 通过最大化检测和错误报警概率之间的差异来适应地确定循环增益.
主要成果:
- 与现有方法相比,A-CLEAN-SC在镜像抑制方面表现出优异的性能.
- 该算法有效地提高了弱目标的检测能力.
- 拟议的方法显示性能有所改善,特别是在转向向量不匹配条件下.
结论:
- A-CLEAN-SC有效地解决了在DOA估计中港/右歧视的挑战.
- 该算法在镜子抑制和弱目标检测之间提供了卓越的权衡.
- 对于具有转向向量不匹配的近线性阵列来说,A-CLEAN-SC特别有利.
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