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Efficient Algorithms for Adaptive Capon and APES Spectral Estimation

机译:自适应Capon和APES频谱估计的高效算法

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In this paper fast algorithms for adaptive Capon and amplitude and phase estimation (APES) methods for spectral analysis of time varying signals, are derived. Fast, stable, nonrecursive formulae are derived, based on time shifting properties of the pertinent variables. As a consequence, efficient frequency domain recursive least squares (RLS) based, as well as fast RLS based algorithms for the adaptive estimation of the power spectra are developed. Stability issues of the frequency domain estimators are considered, and stabilization procedures are proposed. The computational complexity of the proposed algorithms is lower than relevant existing methods. The performance of the proposed algorithms is demonstrated through extensive simulations.
机译:本文推导了自适应Capon的快速算法以及时变信号频谱分析的幅度和相位估计(APES)方法。基于相关变量的时移特性,得出了快速,稳定,非递归的公式。因此,开发了基于有效频域递归最小二乘(RLS)以及基于快速RLS的功率谱自适应估计算法。考虑了频域估计器的稳定性问题,并提出了稳定程序。所提出的算法的计算复杂度低于相关的现有方法。通过广泛的仿真证明了所提出算法的性能。

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