基于非均勻陣列的波達(dá)方向估計(jì)技術(shù)研究
發(fā)布時(shí)間：2019-02-18 11:35
【摘要】：波達(dá)方向(DOA)估計(jì)是信號處理領(lǐng)域的研究熱點(diǎn)之一,這一技術(shù)應(yīng)用廣泛,在通信、雷達(dá)等領(lǐng)域發(fā)揮著越來越重要的作用。在過去的幾十年里人們不斷提出了一系列高效的DOA估計(jì)算法。近幾年來,隨著壓縮感知理論的不斷成熟和廣泛應(yīng)用,基于稀疏重構(gòu)技術(shù)的DOA估計(jì)算法受到更多的關(guān)注和研究。使用均勻線陣估計(jì)信號的波達(dá)方向時(shí),陣列的自由度直接受限于陣元個(gè)數(shù),采用空間平滑技術(shù)處理相關(guān)/相干信號則會進(jìn)一步導(dǎo)致陣列孔徑變小、分辨率降低以及自由度損失。由于非均勻陣列能夠獲得更大的陣列孔徑和更高的自由度,并且陣元的擺放位置也具有更大的靈活性,所以研究非均勻陣列的設(shè)計(jì)和相應(yīng)的DOA估計(jì)算法具有很好的實(shí)際意義和應(yīng)用價(jià)值。本文以使用非均勻陣列估計(jì)遠(yuǎn)場窄帶信號的波達(dá)方向?yàn)檠芯磕繕?biāo),主要研究如何設(shè)計(jì)非均勻陣列以提高陣列的自由度,并根據(jù)非均勻陣列的特點(diǎn)設(shè)計(jì)相應(yīng)的DOA估計(jì)算法,對互質(zhì)陣列、嵌套陣列以及部分均勻陣列等方法進(jìn)行了研究和仿真分析。針對相關(guān)/相干信號的DOA估計(jì),提出了兩種基于稀疏重構(gòu)技術(shù)的DOA估計(jì)方法。本論文的主要貢獻(xiàn)和創(chuàng)新點(diǎn)是:1.針對使用非均勻陣列估計(jì)相關(guān)/相干信號的波達(dá)方向問題,提出了一種稀疏重構(gòu)輔助的相關(guān)信號DOA估計(jì)方法。該方法主要利用稀疏重構(gòu)技術(shù)對信號的波達(dá)方向進(jìn)行初始估計(jì)并確定內(nèi)插映射空域,相比于已有的估計(jì)方法,本方法具有更高的估計(jì)精度。2.為了達(dá)到既能提高陣列的自由度又能估計(jì)相關(guān)/相干信號的目的,提出了一種基于協(xié)方差的低維度迭代稀疏重構(gòu)算法。與傳統(tǒng)的子空間方法相比,該方法能夠獲得更大的陣列孔徑和更高的自由度,而且該方法比已有的稀疏協(xié)方差算法的計(jì)算復(fù)雜度更小。
[Abstract]:Direction of arrival (DOA) estimation is one of the research hotspots in the field of signal processing. This technology is widely used and plays an increasingly important role in communication, radar and other fields. In the past few decades, a series of efficient DOA estimation algorithms have been proposed. In recent years, with the maturity and wide application of compressed sensing theory, DOA estimation algorithm based on sparse reconstruction technology has received more attention and research. When the DOA of the signal is estimated by uniform linear array, the degree of freedom of the array is directly limited by the number of the array elements. The spatial smoothing technique can further reduce the aperture of the array, reduce the resolution and lose the degree of freedom by using the spatial smoothing technique to process the correlation / coherent signal. Because the non-uniform array can obtain larger aperture and higher degree of freedom of the array, and the position of the array elements is also more flexible, Therefore, it has good practical significance and application value to study the design of non-uniform array and the corresponding DOA estimation algorithm. In this paper, the direction of arrival (DOA) of far-field narrow-band signals is estimated by using non-uniform arrays as the research object. This paper mainly studies how to design non-uniform arrays to improve the degree of freedom of the arrays, and designs the corresponding DOA estimation algorithm according to the characteristics of non-uniform arrays. The methods of mass array, nested array and partial uniform array are studied and simulated. For the DOA estimation of correlated / coherent signals, two DOA estimation methods based on sparse reconstruction technique are proposed. The main contributions and innovations of this paper are as follows: 1. To solve the problem of estimating the direction of arrival (DOA) of correlation / coherent signals using non-uniform arrays, a sparse reconstruction aided DOA estimation method for correlated signals is proposed. This method mainly uses sparse reconstruction technique to estimate the DOA of the signal and determine the interpolation mapping spatial domain. Compared with the existing estimation methods, the proposed method has a higher estimation accuracy. 2. In order to improve the degree of freedom of the array and estimate the correlation / coherent signals, a low dimensional iterative sparse reconstruction algorithm based on covariance is proposed. Compared with the traditional subspace method, this method can obtain larger array aperture and higher degree of freedom, and the computational complexity of this method is less than that of the existing sparse covariance algorithm.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN911.7
本文編號：2425792
[Abstract]:Direction of arrival (DOA) estimation is one of the research hotspots in the field of signal processing. This technology is widely used and plays an increasingly important role in communication, radar and other fields. In the past few decades, a series of efficient DOA estimation algorithms have been proposed. In recent years, with the maturity and wide application of compressed sensing theory, DOA estimation algorithm based on sparse reconstruction technology has received more attention and research. When the DOA of the signal is estimated by uniform linear array, the degree of freedom of the array is directly limited by the number of the array elements. The spatial smoothing technique can further reduce the aperture of the array, reduce the resolution and lose the degree of freedom by using the spatial smoothing technique to process the correlation / coherent signal. Because the non-uniform array can obtain larger aperture and higher degree of freedom of the array, and the position of the array elements is also more flexible, Therefore, it has good practical significance and application value to study the design of non-uniform array and the corresponding DOA estimation algorithm. In this paper, the direction of arrival (DOA) of far-field narrow-band signals is estimated by using non-uniform arrays as the research object. This paper mainly studies how to design non-uniform arrays to improve the degree of freedom of the arrays, and designs the corresponding DOA estimation algorithm according to the characteristics of non-uniform arrays. The methods of mass array, nested array and partial uniform array are studied and simulated. For the DOA estimation of correlated / coherent signals, two DOA estimation methods based on sparse reconstruction technique are proposed. The main contributions and innovations of this paper are as follows: 1. To solve the problem of estimating the direction of arrival (DOA) of correlation / coherent signals using non-uniform arrays, a sparse reconstruction aided DOA estimation method for correlated signals is proposed. This method mainly uses sparse reconstruction technique to estimate the DOA of the signal and determine the interpolation mapping spatial domain. Compared with the existing estimation methods, the proposed method has a higher estimation accuracy. 2. In order to improve the degree of freedom of the array and estimate the correlation / coherent signals, a low dimensional iterative sparse reconstruction algorithm based on covariance is proposed. Compared with the traditional subspace method, this method can obtain larger array aperture and higher degree of freedom, and the computational complexity of this method is less than that of the existing sparse covariance algorithm.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN911.7
【參考文獻(xiàn)】
相關(guān)期刊論文 前2條
1 林波;張?jiān)鲚x;朱炬波;;基于壓縮感知的DOA估計(jì)稀疏化模型與性能分析[J];電子與信息學(xué)報(bào);2014年03期
2 熊波;李國林;尚雅玲;高云劍;;信號相關(guān)性與DOA估計(jì)[J];電子科技大學(xué)學(xué)報(bào);2007年05期
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