發(fā)布時(shí)間：2018-04-02 11:14

  本文選題：陣列信號(hào)處理　切入點(diǎn)：波達(dá)方向估計(jì)　出處：《中國(guó)科學(xué)技術(shù)大學(xué)》2017年碩士論文

【摘要】：波達(dá)方向(DOA)估計(jì)是陣列信號(hào)處理的一個(gè)重要研究分支,由于其在雷達(dá)、通信、聲吶、會(huì)議系統(tǒng)等多種領(lǐng)域的廣泛應(yīng)用,使得波達(dá)方向估計(jì)在過去的半個(gè)多世紀(jì)有著快速的發(fā)展。在現(xiàn)實(shí)環(huán)境中,由于山脈、城市建筑反射產(chǎn)生的多徑效應(yīng)和軍事上的人為電磁干擾,使得相干信號(hào)大量存在,傳統(tǒng)的用于解相干的算法是將所有相干信號(hào)放在一起處理,陣列孔徑損失較大,這會(huì)很大程度限制陣列能處理的相干信號(hào)數(shù)量和DOA估計(jì)精度。此外,實(shí)際應(yīng)用中的陣列天線不可避免的存在各種誤差,這會(huì)導(dǎo)致DOA估計(jì)性能嚴(yán)重下降。因此,研究有誤差條件下的DOA估計(jì)算法不僅具有重要的理論意義,而且還具有很重要的實(shí)用價(jià)值。本文通過研究均勻線陣下的相干信號(hào)分組波達(dá)方向估計(jì),提出了一些更為有效的算法,具體的工作如下:1.提出了基于前向空間平滑的相干信號(hào)序貫分組波達(dá)方向估計(jì)算法,根據(jù)組內(nèi)相干信號(hào)的個(gè)數(shù)從少到多依次分組估計(jì)。首先估計(jì)信號(hào)數(shù)最少的那組相干信號(hào)的DOA,并估計(jì)這組相干信號(hào)的衰落系數(shù),利用斜投影算子將這組相干信號(hào)的成分從陣列協(xié)方差矩陣中去除,然后估計(jì)信號(hào)數(shù)第二少的那組相干信號(hào),直到所有組相干信號(hào)估計(jì)完為止。此外,進(jìn)一步研究了基于前后向空間平滑算法的分組提升DOA估計(jì)精度的改進(jìn)算法,通過斜投影算子將每組相干信號(hào)的成分從陣列協(xié)方差矩陣中單獨(dú)提取出來,利用更多子陣的前后向空間平滑進(jìn)一步提升每組相干信號(hào)的估計(jì)精度。通過仿真實(shí)驗(yàn)驗(yàn)證提出的算法在陣元數(shù)少、信噪比低、快拍數(shù)少、信號(hào)數(shù)多的情形下具有較高的DOA估計(jì)性能。2.提出了互耦誤差下的相干信號(hào)序貫分組波達(dá)方向估計(jì)算法。利用均勻線陣的特點(diǎn)以及互耦誤差與間距的關(guān)系,可將陣列兩端的陣元看作輔助陣元,中間子陣具有相同的互耦環(huán)境,通過中間子陣將互耦系數(shù)等效到衰落系數(shù),這樣可以忽略互耦的影響。因此,可將基于前向空間平滑的相干信號(hào)序貫分組波達(dá)方向估計(jì)算法用于中間子陣,實(shí)現(xiàn)互耦誤差下的相干信號(hào)序貫分組DOA估計(jì)。3.提出了互耦誤差下的獨(dú)立信號(hào)和相干信號(hào)波達(dá)方向估計(jì)算法。利用獨(dú)立信號(hào)不需要空間平滑就與噪聲子空間正交的特點(diǎn),通過中間子陣將互耦系數(shù)等效到信號(hào)能量上,先估計(jì)出獨(dú)立信號(hào)的DOA,利用已經(jīng)估計(jì)出的DOA進(jìn)一步估計(jì)出互耦系數(shù),然后將獨(dú)立信號(hào)的成分從陣列協(xié)方差矩陣去除并補(bǔ)償互耦系數(shù)后,序貫分組估計(jì)相干信號(hào)的DOA。
[Abstract]:DOA estimation is an important branch of array signal processing, because of its wide application in radar, communication, sonar, conference system and other fields. The DOA estimation has developed rapidly in the past half century. In the real world, because of the multipath effect caused by the reflection of mountains, urban buildings and the military artificial electromagnetic interference, the coherent signals exist in large quantities. The traditional algorithm for decoherence is to process all coherent signals together, and the aperture loss of the array is large, which will greatly limit the number of coherent signals and the DOA estimation accuracy that the array can process. In practical applications, there are inevitable errors in array antennas, which will lead to a serious deterioration of DOA estimation performance. Therefore, it is not only of theoretical significance to study the DOA estimation algorithm under the condition of errors. It is also of great practical value. In this paper, some more effective algorithms are proposed by studying the DOA estimation of coherent signals under uniform linear array. The main work is as follows: 1. A direction of arrival (DOA) estimation algorithm for coherent signals based on forward spatial smoothing is proposed. The number of coherent signals in a group is estimated from small to many. First, the load of the group of coherent signals with the least number of signals is estimated, and the fading coefficients of the coherent signals are estimated. The component of the coherent signal is removed from the array covariance matrix by oblique projection operator, and the second least coherent signal is estimated until all the coherent signals are estimated. An improved algorithm for improving the accuracy of DOA estimation based on the forward and backward spatial smoothing algorithm is further studied. The components of each coherent signal are extracted from the array covariance matrix by oblique projection operator. The estimation accuracy of each group of coherent signals is further improved by using forward and backward spatial smoothing of more subarrays. Simulation results show that the proposed algorithm has less array elements, lower signal-to-noise ratio and fewer rapid-beat numbers. When the number of signals is large, the performance of DOA estimation is higher. 2. An algorithm for estimating the direction of arrival of coherent signals by sequential grouping with mutual coupling error is proposed. The characteristics of uniform linear array and the relationship between mutual coupling error and spacing are used. The element at both ends of the array can be regarded as the auxiliary element, and the intermediate subarray has the same mutual coupling environment. The mutual coupling coefficient can be equivalent to the fading coefficient by the intermediate subarray, so the influence of mutual coupling can be ignored. The direction of arrival (DOA) estimation algorithm of coherent signals based on forward spatial smoothing can be used in intermediate subarrays. The coherent signal sequential block DOA estimation under mutual coupling error is realized. A direction of arrival estimation algorithm for independent signal and coherent signal under mutual coupling error is proposed. The independent signal is orthogonal to the noise subspace without spatial smoothing. The mutual coupling coefficient is equivalent to the signal energy through the intermediate submatrix, the load of the independent signal is estimated first, and the mutual coupling coefficient is further estimated by using the estimated DOA. Then the component of the independent signal is removed from the array covariance matrix and the mutual coupling coefficient is compensated, then the DOA of the coherent signal is estimated by sequential grouping.
【學(xué)位授予單位】：中國(guó)科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN911.7

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