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arXiv 1910.03095eess.SP
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一般秩信号模型下的混合稀疏阵列波束形成设计

Hybrid Sparse Array Beamforming Design for General Rank Signal Models

Syed A. Hamza, Moeness G. Amin

摘要:

本文考虑稀疏阵列设计接收波束形成实现最大的信号与干扰加噪声比(MaxSINR)的单点源和多点源,在干扰活跃的环境中工作。与现有的稀疏设计方法,无论是处理结构化的环境无关或非结构化的环境相关的阵列,我们的方法是一种混合的方法,并寻求一个完整的增强阵列,优化波束形成器的性能。这种方法被证明是重要的有限孔径,约束传感器放置的可能的均匀网格点的数量。该问题被表述为二次约束二次规划(QCQP),其中代价函数用波束形成器权向量的加权l_1范数平方进行惩罚。仿真结果表明,所提出的算法的有效性阵列配置的情况下,单秩和一般的信号相关矩阵。所提出的稀疏阵列,常用的均匀阵列,阵列通过其他设计方法,和阵列的设计没有扩展性约束的性能比较。

英文摘要:

The paper considers sparse array design for receive beamforming achieving maximum signal-to-interference plus noise ratio (MaxSINR) for both single point source and multiple point sources, operating in an interference active environment. Unlike existing sparse design methods which either deal with structured environment-independent or non-structured environment-dependent arrays, our method is a hybrid approach and seeks a full augumentable array that optimizes beamformer performance. This approach proves important for limited aperture that constrains the number of possible uniform grid points for sensor placements. The problem is formulated as quadratically constraint quadratic program (QCQP), with the cost function penalized with weighted l_1-norm squared of the beamformer weight vector. Simulation results are presented to show the effectiveness of the proposed algorithms for array configurability in the case of both single and general rank signal correlation matrices. Performance comparisons among the proposed sparse array, the commonly used uniform arrays, arrays obtained by other design methods, and arrays designed without the augmentability constraint are provided.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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