發(fā)布時(shí)間：2018-04-25 05:28

  本文選題：非均勻噪聲 + Khatri-Rao子空間　； 參考：《電子科技大學(xué)》2017年碩士論文

【摘要】：正交頻分復(fù)用(Orthogonal Frequency Division Multiplexing,OFDM)是一種效率很高的多載波調(diào)制技術(shù)。因其具有抗頻率選擇性衰落、頻譜利用率高等特點(diǎn),所以備受陣列信號(hào)處理方向的研究人員關(guān)注。如何有效地估計(jì)OFDM信號(hào)的來波方向,已成為陣列信號(hào)處理中一個(gè)新的研究方向。本文考慮實(shí)際工程應(yīng)用的需求,主要圍繞非均勻噪聲情況下和欠定情況下的OFDM信號(hào)波達(dá)方向估計(jì)問題展開研究,具體研究?jī)?nèi)容如下:1、研究了現(xiàn)有的一些寬帶信號(hào)空間測(cè)向算法。如ISM算法、修正的ISM算法以及CSM算法。通過對(duì)這些算法進(jìn)行推導(dǎo)和仿真分析,可知這些算法只適用于信源數(shù)小于陣元數(shù)情況下的空間測(cè)向。且當(dāng)天線陣元噪聲為非均勻噪聲時(shí),這些算法都會(huì)產(chǎn)生性能惡化。這為后續(xù)研究OFDM信號(hào)波達(dá)方向估計(jì)算法提供了理論基礎(chǔ)和參考依據(jù)。2、針對(duì)非均勻噪聲背景下,一些經(jīng)典的測(cè)向算法可能會(huì)產(chǎn)生估計(jì)偏差增大、角度分辨率下降以及出現(xiàn)偽峰等問題,提出了基于MUSIC-Like算法的OFDM信號(hào)空間測(cè)向算法。該算法先利用虛擬陣列平移方法進(jìn)行解相關(guān)處理,再通過波束形成技術(shù)以及拉格朗日乘子法技術(shù),求出每個(gè)子窄帶的最優(yōu)空域?yàn)V波器的權(quán)向量,最后利用加權(quán)求平均運(yùn)算得到測(cè)向的空間譜。仿真結(jié)果表明,該算法不僅在非均勻噪聲背景有較好的估計(jì)精度,而且能估計(jì)出相干信號(hào)。此外,該算法實(shí)現(xiàn)了信源未知條件下的空間測(cè)向,且不依賴于子空間分解。這就避免了因錯(cuò)誤估計(jì)信源數(shù)而對(duì)OFDM信號(hào)波達(dá)方向估計(jì)性能產(chǎn)生的影響,提高了信號(hào)波達(dá)方向估計(jì)的分辨率。3、針對(duì)欠定情況下,即信源數(shù)大于陣元數(shù),大多數(shù)現(xiàn)有的算法(如ISM算法等)不能估計(jì)出目標(biāo)的波達(dá)方向的問題,提出了基于稀疏重構(gòu)的Khatri-Rao子空間OFDM信號(hào)空間測(cè)向算法。該算法首先針對(duì)二階嵌套陣列提出了一種改進(jìn)的嵌套陣列用于提高陣列的自由度;然后結(jié)合Khatri-Rao積構(gòu)造一個(gè)新的虛擬陣列流形矩陣;最后利用稀疏重構(gòu)算法進(jìn)行空間測(cè)向。仿真結(jié)果表明,基于稀疏重構(gòu)的KR子空間OFDM信號(hào)空間測(cè)向算法可以在欠定和非均勻噪聲背景下較好地估計(jì)出信號(hào)的波達(dá)方向,并且其估計(jì)精度較現(xiàn)有算法有較大提高。
[Abstract]:Orthogonal Frequency Division Multiplexing (OFDM) is an efficient multicarrier modulation technique. Because of its characteristics of anti-frequency selective fading and high spectral efficiency, it has attracted the attention of researchers in the field of array signal processing. How to estimate the direction of OFDM signal effectively has become a new research direction in array signal processing. In this paper, the direction of arrival (DOA) estimation of OFDM signals in the case of non-uniform noise and underdetermined signal is studied in consideration of the requirements of practical engineering applications. The specific research contents are as follows: 1, and some existing spatial direction-finding algorithms for wideband signals are studied. Such as ISM algorithm, modified ISM algorithm and CSM algorithm. Through the derivation and simulation analysis of these algorithms, it can be concluded that these algorithms are only suitable for spatial direction finding when the number of sources is less than the number of array elements. When the noise of antenna array is nonuniform, the performance of these algorithms will deteriorate. This provides a theoretical basis and reference basis for further research on DOA estimation of OFDM signals. For non-uniform noise background, some classical direction-finding algorithms may cause an increase in estimation deviation. The spatial direction finding algorithm of OFDM signal based on MUSIC-Like algorithm is proposed. The algorithm first uses the virtual array translation method to decorrelate, and then through the beamforming technology and Lagrange multiplier method, the weight vector of each sub-narrow band optimal spatial filter is obtained. Finally, the spatial spectrum of direction finding is obtained by weighted averaging operation. The simulation results show that the proposed algorithm not only has good estimation accuracy in non-uniform noise background, but also can estimate coherent signals. In addition, the algorithm realizes spatial direction finding under unknown source conditions, and does not depend on subspace decomposition. This avoids the influence on the DOA estimation performance of OFDM signal due to the wrong estimation of the number of sources, and improves the resolution of DOA estimation of the OFDM signal. In the case of uncertainty, the number of sources is larger than the number of array elements. Most of the existing algorithms (such as ISM algorithm) can not estimate the DOA of the target. A spatial direction finding algorithm of Khatri-Rao subspace OFDM signal based on sparse reconstruction is proposed. Firstly, an improved nested array is proposed to improve the degree of freedom of the second order nested array, then a new virtual array manifold matrix is constructed based on Khatri-Rao product. Finally, the sparse reconstruction algorithm is used for spatial direction finding. The simulation results show that the KR subspace OFDM signal spatial direction finding algorithm based on sparse reconstruction can estimate the direction of arrival (DOA) of the signal under the background of unsteady and non-uniform noise, and its estimation accuracy is much higher than that of the existing algorithms.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.53

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本文編號(hào)：1799978