基于四階累積量的后驗(yàn)稀疏約束迭代DOA估計(jì)方法
A FOURTH-ORDER CUMULANT BASED RECURSIVE APPROACH TO DOA ESTIMATION WITH SPARSITY CONSTRAINT
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摘要: 子空間DOA估計(jì)方法的一個(gè)缺點(diǎn)是在子空間分解過程中難以利用信號(hào)的相關(guān)信息或有關(guān)DOA估計(jì)的先驗(yàn)信息改善DOA估計(jì)的性能。該文結(jié)合子空間方法和四階累積量矩陣擬合方法,利用信號(hào)四階累積量矩陣的結(jié)構(gòu)信息與信號(hào)間相互獨(dú)立的先驗(yàn)信息,研究了一種新的不相關(guān)窄帶信號(hào)波達(dá)方向(DOA)的迭代估計(jì)方法。理論分析和仿真實(shí)驗(yàn)結(jié)果表明,這種迭代DOA估計(jì)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(jì)。
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關(guān)鍵詞:
- 四階累積量; 稀疏約束; 子空間; DOA估計(jì)
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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