本文選題：到達角估計　切入點：協(xié)方差擬合　出處：《上海交通大學學報》2017年09期 　論文類型：期刊論文

【摘要】：為進行高分辨到達角(DOA)估計的同時避免稀疏類算法的不足,提出了協(xié)方差擬合旋轉不變子空間信號參數(shù)估計(ESPRIT)算法.首先將協(xié)方差擬合準則轉換成半正定規(guī)劃問題,利用凸優(yōu)化進行求解,得到更接近理論值的信號協(xié)方差矩陣;然后對估計的信號協(xié)方差矩陣進行特征分解,利用信號子空間和噪聲子空間特征值的差異估計信源個數(shù);最后利用子空間旋轉不變性反解出未知DOA.仿真實驗從DOA估計精度、分辨率等方面驗證了該算法的有效性,較傳統(tǒng)ESPRIT算法具有更高的DOA估計分辨率并且受相干信源影響小;與稀疏類算法相比,不依賴先驗信息以及避免了網(wǎng)格失配問題.
[Abstract]:In order to carry out high resolution DOA estimation and avoid the shortage of sparse algorithms, a covariance fitting rotation invariant subspace signal parameter estimation algorithm is proposed. The covariance fitting criterion is first converted into a positive semidefinite programming problem. The signal covariance matrix, which is closer to the theoretical value, is solved by convex optimization, then the estimated signal covariance matrix is decomposed and the number of information sources is estimated by using the difference between the eigenvalues of the signal subspace and the noise subspace. Finally, the unknown DOA is solved by subspace rotation invariance. The simulation results show that the proposed algorithm is effective in terms of DOA estimation accuracy and resolution. Compared with the traditional ESPRIT algorithm, the proposed algorithm has higher DOA resolution and is less affected by coherent sources. Compared with sparse class algorithm, it does not rely on prior information and avoids mesh mismatch problem.
【作者單位】： 空軍預警學院;
【基金】：國家自然科學基金(61401504) 軍內計劃科研項目(2015×××) 湖北省自然科學基金(2016CFB288)資助
【分類號】：TN911.7
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本文編號：1593330