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Instrumental variable subspace tracking with applications to sensor array processing and frequency estimation

机译:工具变量子空间跟踪及其在传感器阵列处理和频率估计中的应用

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Recursive methods for subspace tracking with applications to 'on-line' direction of arrival estimation, have lately drawn considerable interest. Instrumental variable (IV) generalizations of the projection approximation subspace tracking (PAST) algorithm are proposed. The IV-approach is motivated by the fact that PAST delivers biased estimates when the noise vectors are not spatially white. The resulting basic IV-algorithm has a computational complexity of 3mn+O(n/sup 2/) complex multiplications, where m is the dimension of the measurement vector and n is the subspace dimension. The performance of the proposed algorithms in tracking sinusoids in colored noise is illustrated by computer simulations.
机译:用于子空间跟踪的递归方法及其在到达估计的“在线”方向上的应用近来引起了人们的极大兴趣。提出了投影近似子空间跟踪(PAST)算法的工具变量(IV)概括。 IV方法是受以下事实激励的:当噪声矢量在空间上不是白色时,PAST会提供有偏差的估计。所得的基本IV算法的计算复杂度为3mn + O(n / sup 2 /)复数乘法,其中m为测量向量的维数,n为子空间维数。计算机仿真表明了所提出算法在彩色噪声中跟踪正弦曲线的性能。

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