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題名 | Adaptive Eigendecomposition Algorithms for Eigenstructure-Based Array Signal Processing=適用於特徵結構陣列信號處理之適應性特徵分解演算法則 |
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作者 | 張麗娜; Chang, Lena; |
期刊 | 中國工程學刊 |
出版日期 | 19970700 |
卷期 | 20:4 1997.07[民86.07] |
頁次 | 頁365-375 |
分類號 | 448.5 |
語文 | eng |
關鍵詞 | 特徵分解; 特徵結構; Eigendecomposition; Eigenstructure; |
中文摘要 | 本論文首先提出一正向演算法則以適應性調整連續取樣自相關矩陣之特徵分量。 此正向適應性特徵分解演算法則(FOAE)是依據交替遞迴調整之技術,此法可減少特徵分解之 計算複雜度。如一MXM附矩陣,FOAE每衣遞迴調整信號子空間之特徵分量需O(Mq)複數運算 量,其中q表訊號源數目。接著,針對一對稱型之天線陣列,利用其自相關矩陣Hermitian persymmetry之特性,提出一實數正反向適應性特徵分解演算法則(RFBAE)。此法每次遞迴調 整信號子空間之特徵分量僅需O(Mq)實數運算量。此外,將FOAE及RFBAE應用於方位估測、 追蹤及波束形成器之設計,由模擬結果驗證本論文所提之演算法則收斂快速,且RFBAE效能 較FOAE佳。 |
英文摘要 | This paper first presents a forward-only algorithm for adaptive eigendecomposition of a continuously updated sample correlation matrix for arbitrary geometry arrays. The proposed forward-only adaptive eigendecomposition (FOAE) algorithm is based on an alternate iteration technique which can alleviate the computation complexity of the standard eigendecomposition. For an M×M matrix, the FOAF algorithm requires O(Mq) complex operations per iteration to adjust the eigencomponents of the signal subspace, where q is the signal sub-space dimension. Then, for a symmetrically distributed antenna array, we exploit the Hermitian persymmetric property of the correlation matrix to develop a real-valued forward-backward adaptive eigendecomposition (RFBAE) algorithm. The proposed RFBAE algorithm requires only O(Mq) real operations in each iteration. Moreover, the FOAE and RFBAE algorithms are applied to estimate or track the angles of arrival and design the eigenspace-based beamformer. Simulation results confirm the fast convergence rate of the proposed algorithms and the RFBAE algorithm performs better than the FOAE algorithm. |
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