互質(zhì)陣中基于降維求根的波達(dá)角估計(jì)算法
doi: 10.11999/JEIT171087
基金項(xiàng)目:
國家自然科學(xué)基金(61601167, 61771182), 中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金資助(2018B15914)
Reduced-dimensional Root Finding Based Direction of Arrival Estimation for Coprime Array
Funds:
The National Natural Science Foundation of China (61601167, 61771182), The Fundamental Research Funds for the Central Universities (2018B15914)
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摘要: 該文提出互質(zhì)陣中基于降維求根的波達(dá)角(DOA)估計(jì)算法?；ベ|(zhì)陣包含兩個(gè)稀疏均勻線性子陣，擁有互質(zhì)的陣元間距和陣元數(shù)目。該算法基于子陣間的互協(xié)方差，利用較長子陣中的旋轉(zhuǎn)不變性擴(kuò)展較短子陣的虛擬孔徑。然后通過矩陣分塊構(gòu)造噪聲子空間，并將來自兩個(gè)子陣的2維參數(shù)估計(jì)問題降維為1維求根問題，獲得自動配對的2維模糊參數(shù)估計(jì)。最后由這2維模糊參數(shù)可恢復(fù)出兩組參數(shù)，根據(jù)互質(zhì)性從兩組參數(shù)估計(jì)的交集中可以獲得無模糊的高分辨率DOA估計(jì)。相比互質(zhì)陣中的聯(lián)合多重信號分類(MUSIC)算法和聯(lián)合旋轉(zhuǎn)不變技術(shù)(ESPRIT)算法，該算法無需特征分解，復(fù)雜度低，但可獲得更精確的DOA估計(jì)，處理更多的信源，并且對色噪聲有更強(qiáng)的魯棒性。多個(gè)仿真結(jié)果均驗(yàn)證了所提算法的有效性。
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關(guān)鍵詞:
- 波達(dá)角估計(jì) /
- 互質(zhì)陣 /
- 降維求根 /
- 孔徑擴(kuò)展
Abstract: A Direction of Arrival (DOA) estimation method based on reduced-dimensional polynomial root finding technique is proposed for coprime array. Coprime array has two uniform linear subarrays with coprime inter-element spacing and antenna number. Based on the cross covariance matrix of the subarrays, the proposed method exploits the rotational invariance within the longer subarray to extend the aperture of the shorter one. After constructing the noise subspace via matrix partition and reducing the two dimensional parameter estimation problem into one dimensional root finding, automatically paired two dimensional parameters can be estimated. Finally, unambiguous DOA is determined from the intersections of the two groups of estimations, which are generated from the previously obtained two dimensional parameters. In contrast to combined MUltiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) for coprime array, the proposed algorithm achieves improved DOA estimation results and increased identifiable source number with reduced computation complexity. Furthermore, it is robust to spatial color noise. Multiple simulation results verify the effectiveness of the proposed approach.-
Key words:
- DOA estimation /
- Coprime array /
- Reduced-dimensional root finding /
- Aperture extension
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