βopt, and the solving for each parameter of the vector βopt by minimizing the expected power of the array output signal Y. A robustness-control transformation is then applied to the vector p to provide a robust vector βopt wherein the robustness-control transformation identifies and reduces target canceling components of the vector βopt while preserving non-target canceling components. Finally, the weight vector indicative of the filter tap weights is formed as a function of the vector βopt. Notably, the present invention separates the robustness constraining process from the beamforming power minimization, in contrast to prior art techniques which combine the robustness constraint into the beamforming power minimization. The present invention uses a direct and flexible robustness control mechanism to yield a beamformer that provides good performance and is robust to a wide variety of adverse conditions."/> Location-estimating, null steering (LENS) algorithm for adaptive array processing
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Location-estimating, null steering (LENS) algorithm for adaptive array processing

机译:自适应阵列处理的位置估计,空值控制(LENS)算法

摘要

An adaptive multiple-tap frequency domain digital filter processes an input signal vector X from an plurality of spatially separated transducers that detect energy from a plurality of sources including a target energy source and at least one non-target energy source. The filter receives and processes the input signal vector X to attenuate noise from non-target sources and provides an output signal vector Y. Tap weights WN for the filter are selected by first parameterizing each of the tap weights WN, such that each of the tap weights WN is characterized by a vector of parameters βopt, and the solving for each parameter of the vector βopt by minimizing the expected power of the array output signal Y. A robustness-control transformation is then applied to the vector p to provide a robust vector βopt wherein the robustness-control transformation identifies and reduces target canceling components of the vector βopt while preserving non-target canceling components. Finally, the weight vector indicative of the filter tap weights is formed as a function of the vector βopt. Notably, the present invention separates the robustness constraining process from the beamforming power minimization, in contrast to prior art techniques which combine the robustness constraint into the beamforming power minimization. The present invention uses a direct and flexible robustness control mechanism to yield a beamformer that provides good performance and is robust to a wide variety of adverse conditions.
机译:自适应多抽头频域数字滤波器处理来自多个空间上分开的换能器的输入信号矢量X,这些换能器从包括目标能源和至少一个非目标能源的多个源中检测能量。滤波器接收并处理输入信号矢量X,以衰减来自非目标源的噪声,并提供输出信号矢量Y。通过首先参数化每个抽头权重来选择滤波器的抽头权重W N W N ,这样每个抽头权重W N 的特征在于参数β opt的向量,并通过最小化数组输出信号Y的期望功率来求解向量β opt 的每个参数。然后将控制变换应用于向量p,以提供鲁棒矢量β opt ,其中鲁棒控制变换可识别并减少向量的目标抵消分量β opt ,同时保留非目标抵消组件。最后,根据向量β opt 形成表示滤波器抽头权重的权重向量。显然,与将鲁棒性约束组合到波束形成功率最小化的现有技术相比,本发明将鲁棒性约束过程与波束形成功率最小化分开。本发明使用直接且灵活的鲁棒性控制机制来产生提供良好性能并对各种不利条件鲁棒的波束形成器。

著录项

  • 公开/公告号US7254199B1

    专利类型

  • 公开/公告日2007-08-07

    原文格式PDF

  • 申请/专利权人 JOSEPH G. DESLOGE;

    申请/专利号US19990396175

  • 发明设计人 JOSEPH G. DESLOGE;

    申请日1999-09-14

  • 分类号H04B1/10;

  • 国家 US

  • 入库时间 2022-08-21 21:00:37

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