被动声呐盲分离自适应-自适应波束形成算法研究

钱宇宁; 曹欣荣; 陈亚伟; 孙俊; 张翔宇

doi:10.11999/JEIT170099

被动声呐盲分离自适应-自适应波束形成算法研究

doi: 10.11999/JEIT170099

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出版历程
- 收稿日期: 2017-01-24
- 修回日期: 2017-05-31
- 刊出日期: 2017-10-19

Research on Adaptive-adaptive Beamforming Algorithm Based on Blind Separation for Passive Sonar

摘要

摘要: 基于自适应-自适应方法在大规模被动声呐阵列降维处理上的应用需求，该文提出一种基于盲分离的自适应-自适应波束形成降维算法。该算法将独立成分分析方法与自适应-自适应降维方法有机结合，通过独立成分分析在不预知干扰来向的条件下自适应地估计干扰源的导向矢量，并进一步采用自适应-自适应方法对阵列信号进行波束空间降维，最后采用稳健自适应方法进行波束形成处理。仿真实验验证了该算法能够有效降低大规模阵列自适应处理的计算量，其波束形成效果以及对误差的稳健性与全阵自适应方法相近。
- 大规模声呐阵列 /
- 降维 /
- 独立成分分析 /
- 自适应-自适应
Abstract: Due to the application requirement of adaptive-adaptive dimension reduction method in large-scale passive sonar array, a blind separation adaptive-adaptive beamforming algorithm is presented, which combines the Independent Component Analysis (ICA) with the traditional adaptive-adaptive approach. The ICA approach is firstly used to obtain the steering vectors of signal sources without prior information of signal direction. Then, the adaptive-adaptive approach is utilized to reduce signal dimension in beam space and robust adaptive approach is finally used for beamforming. The simulation studies verify the effectiveness of the proposed algorithm for computation burden reduction of large-scale array adaptive processing. Furthermore, the beamforming results and robustness of the proposed algorithm is similar to that of full- array adaptive method.
- Large-scale sonar array /
- Dimension reduction /
- Independent Component Analysis (ICA) /
- Adaptive- adaptive

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