二阶虚拟阵列权函数的计算及估计性能分析

Payal Gupta, M. Agrawal
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引用次数: 1

摘要

在传感器阵列信号处理中,增加从给定传感器阵列中处理的源的数量是一个重要的问题,也是许多研究人员感兴趣的问题。基于虚拟阵列的方法也解决了这个问题,其中协方差和累积滞后提供了一个虚拟传感器。其中,影响参数估计精度和延迟的一个重要参数是权函数。权重函数定义为虚拟阵列中每个虚拟传感器出现的频率。给出了虚阵对应于线性阵的近似表达式。本文还对虚拟阵列的权函数进行了分析计算,并研究了权函数对参数估计的影响。仿真结果表明,采用高权重函数可显著提高参数估计精度。
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Computation of Weight Function of 2qth Order Virtual Array to Analyse the Estimation Performance
Increasing the number of sources to be processed from a given array of sensors is an important problem in sensor array signal processing and of interest to many researchers. This problem has also been tackled with the virtual array based approach where the covariance and cumulant lags provide a virtual sensor. Here, an important parameter which affects the parameter estimation accuracy and latency is weight function. The weight function is defined as the frequency of occurrence of each virtual sensor in the virtual array. We provide the close-form expression of virtual array corresponding to linear array. We have also analytically evaluated the weight function of virtual array and have also studied the effect of the weight function on parameter estimation. Simulation results show the parameter estimation accuracy is significantly improve with high weight function.
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