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基于四階累積量的后驗稀疏約束迭代DOA估計方法

萬群,  楊萬麟

萬群, 楊萬麟. 基于四階累積量的后驗稀疏約束迭代DOA估計方法[J]. 電子與信息學報, 2001, 23(11): 1123-1128.
引用本文: 萬群, 楊萬麟. 基于四階累積量的后驗稀疏約束迭代DOA估計方法[J]. 電子與信息學報, 2001, 23(11): 1123-1128.
Wan Qun, Yang Wanlin . A FOURTH-ORDER CUMULANT BASED RECURSIVE APPROACH TO DOA ESTIMATION WITH SPARSITY CONSTRAINT[J]. Journal of Electronics & Information Technology, 2001, 23(11): 1123-1128.
Citation: Wan Qun, Yang Wanlin . A FOURTH-ORDER CUMULANT BASED RECURSIVE APPROACH TO DOA ESTIMATION WITH SPARSITY CONSTRAINT[J]. Journal of Electronics & Information Technology, 2001, 23(11): 1123-1128.

基于四階累積量的后驗稀疏約束迭代DOA估計方法

A FOURTH-ORDER CUMULANT BASED RECURSIVE APPROACH TO DOA ESTIMATION WITH SPARSITY CONSTRAINT

  • 摘要: 子空間DOA估計方法的一個缺點是在子空間分解過程中難以利用信號的相關信息或有關DOA估計的先驗信息改善DOA估計的性能。該文結合子空間方法和四階累積量矩陣擬合方法,利用信號四階累積量矩陣的結構信息與信號間相互獨立的先驗信息,研究了一種新的不相關窄帶信號波達方向(DOA)的迭代估計方法。理論分析和仿真實驗結果表明,這種迭代DOA估計方法一般經(jīng)過幾次迭代就能獲得穩(wěn)定的高分辨率DOA估計。
    Abstract: One disadvantage with subspace-based DOA estimate method is that it is difficult to incorporate prior knowledge of the signal correlation into the eigen-decomposition. Herein, an estimator that combines ideas from subspace and four-order cumulant matching method is proposed, which makes it possible to incorporate the prior knowledge of signal correlation and sparsity of the DOA estimation into the estimator. Theoretical analysis and numerical results illustrate the robust and high resolution character of the estimator.
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  • 魏平,肖先賜,李樂民,基于四階累積量特征分解的空間譜估計測向方法,電子科學學刊,1995,17(3),243-249[2]M. Jansson, B. Goransson, B. Ottersten, A subspace method for direction of arrival estimationof uncorrelated emitter signal, IEEE Trans. on SP, 1999, SP-47(3), 945-956.[3]魏平,肖先賜,基于四階累積量的陣列擴展,電子科學學刊,1997,19(6),745-750[4]I.F. Gorodnitsky, B. D. Rao, A recursive weighted norm minimization algorithm and its appli-cation, in Proc. Int. Conf., ASSP, Minneapolis, Apr., 1993, 456-459.[5]B.D. Rao, L. K. K. Delgado, An affine scaling methodology for best basis selection, IEEE Trans.on SP, 1999, SP-47(1), 187-200.[6]P.C. Hansen, Analysis of discrete ill-posed problems by means of L-curve, SIAM Rev., 1992, 34(4), 561-580.[7]I.F. Gorodnitsky, B. D. Rao, Sparse signal reconstruction from limited data using FOCUSS(FOCual Underdetermined System Solver), A re-weighted minimum norm algorithm, IEEE Trans.on SP, 1997, SP-45(3), 600-615.[8]D.A. Linebarger, Redundance averaging with large array, IEEE Trans. on SP, 1993, SP-41(4), 1707-1710.
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出版歷程
  • 收稿日期:  1999-09-29
  • 修回日期:  2000-02-11
  • 刊出日期:  2001-11-19

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