单位圆MVDR波束形成器

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摘要翻译：
对于采用均匀线阵的窄带平波波束形成器，阵列多项式是阵列权重的Z变换。求复平面内单位圆上的阵列多项式，得到波束方向图。单位圆上的多项式零点的位置表示波束模式的零点。对于用ULA测量的平面波信号，集合MVDR多项式零点的位置约束在单位圆上。然而，样本矩阵求逆(SMI)的MVDR多项式零点一般不落在单位圆上。提出的单位圆MVDR（UC MVDR）将SMI MVDR多项式的零点径向投影到单位圆上。这满足了对系综MVDR多项式零点的约束。数值仿真表明，UC MVDR波束形成器比SMI MVDR和对角加载MVDR波束形成器更好地抑制干扰，并提高了白噪声增益(WNG)。
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英文标题：
《Unit circle MVDR beamformer》
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作者：
Saurav R Tuladhar and John R Buck
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最新提交年份：
2016
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Information Theory        信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Mathematics        数学
二级分类：Information Theory        信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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英文摘要：
  The array polynomial is the z-transform of the array weights for a narrowband planewave beamformer using a uniform linear array (ULA). Evaluating the array polynomial on the unit circle in the complex plane yields the beampattern. The locations of the polynomial zeros on the unit circle indicate the nulls of the beampattern. For planewave signals measured with a ULA, the locations of the ensemble MVDR polynomial zeros are constrained on the unit circle. However, sample matrix inversion (SMI) MVDR polynomial zeros generally do not fall on the unit circle. The proposed unit circle MVDR (UC MVDR) projects the zeros of the SMI MVDR polynomial radially on the unit circle. This satisfies the constraint on the zeros of ensemble MVDR polynomial. Numerical simulations show that the UC MVDR beamformer suppresses interferers better than the SMI MVDR and the diagonal loaded MVDR beamformer and also improves the white noise gain (WNG).
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PDF链接：
https://arxiv.org/pdf/1611.02721

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关键词：单位圆 Applications Optimization Experimental information 多项式 阵列 求复 ULA 变换