本文關(guān)鍵詞：改進(jìn)的MUSIC算法在信號(hào)DOA估計(jì)中的研究　出處：《長(zhǎng)安大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 波達(dá)方向估計(jì) MUSIC算法 相干信號(hào) 高斯噪聲

【摘要】：陣列信號(hào)處理技術(shù)成為信號(hào)處理領(lǐng)域的一個(gè)重要的學(xué)科，它在通信、雷達(dá)、聲納、電子對(duì)抗等對(duì)多領(lǐng)域有著極為廣闊的應(yīng)用前景�；陉嚵行盘�(hào)處理的波達(dá)方向（DOA）估計(jì)方法，可以同時(shí)對(duì)空間不同方向上的多個(gè)信號(hào)源實(shí)現(xiàn)高分辨率的方向估計(jì)。經(jīng)過(guò)40過(guò)年的研究，，各國(guó)學(xué)者分析了各種類(lèi)型的算法，信號(hào)波達(dá)方向的研究已經(jīng)越來(lái)越完善。本文采用了理論和計(jì)算仿真實(shí)驗(yàn)相結(jié)合的的方法對(duì)算法和陣列結(jié)構(gòu)的有關(guān)問(wèn)題進(jìn)行了研究。主要工作內(nèi)容如下： 本文從經(jīng)典的MUSIC算法入手，在理想高斯白噪聲條件下，分析了影響MUSIC算法性能的客觀因素并用MATLAB進(jìn)行仿真。由于MUSIC算法在相干信源進(jìn)行估計(jì)時(shí)性能?chē)?yán)重下降甚至是失效，因此，本文基于對(duì)MUSIC算法原理的改進(jìn)，詳細(xì)地介紹了空間平滑法、修正MUSIC算法和基于Toeplitz矩陣重構(gòu)的去相干算法�？臻g平滑法，雖然解決了相干信號(hào)源的問(wèn)題，但是對(duì)陣列孔徑有一定的損失。修正的MUSIC算法，計(jì)算量小而且對(duì)陣列孔徑?jīng)]有損失，而基于Toeplitz矩陣重構(gòu)的去相干算法，不僅有修正MUSIC算法的優(yōu)點(diǎn)，還實(shí)現(xiàn)了少陣元多信源的DOA估計(jì)，并且在低信噪比時(shí)性能表現(xiàn)較好。 在傳統(tǒng)DOA估計(jì)算法的基礎(chǔ)上，對(duì)近幾年DOA估計(jì)中出現(xiàn)的高階累積量信號(hào)分析與處理技術(shù)進(jìn)行了研究。基于高斯色噪聲條件下的DOA估計(jì)做了詳細(xì)的介紹，本文應(yīng)用了基于四階累積量的MUSIC算法，為了去除算法中的大量數(shù)據(jù)冗余，提出了改進(jìn)的四階MUSIC算法。仿真結(jié)果表明，該在未知高斯噪聲下，可以準(zhǔn)確的估計(jì)出信號(hào)的入射角度，且階數(shù)越高，估計(jì)性能越好。
[Abstract]:Array signal processing technology has become an important subject in the field of signal processing, it is in communication, radar, sonar. Electronic countermeasures have a wide application prospect in many fields. The DOA estimation method based on array signal processing is presented. High resolution direction estimation can be achieved for multiple signal sources in different directions at the same time. After 40 years of research, scholars from all over the world have analyzed various kinds of algorithms. The research on the DOA of the signal has become more and more perfect. In this paper, the algorithm and the array structure are studied by combining the theory with the simulation experiment. The main work is as follows: This paper starts with the classical MUSIC algorithm, under the condition of ideal Gao Si white noise. The objective factors that affect the performance of MUSIC algorithm are analyzed and simulated with MATLAB. Because the performance of MUSIC algorithm in the estimation of coherent sources is seriously degraded or even failed. Based on the improvement of MUSIC algorithm, spatial smoothing, modified MUSIC and Toeplitz matrix reconstruction are introduced in detail in this paper. Although the problem of coherent signal source is solved, there is a certain loss to array aperture. The modified MUSIC algorithm has less computation and no loss to array aperture. The decoherence algorithm based on Toeplitz matrix reconstruction not only has the advantage of modified MUSIC algorithm, but also realizes the DOA estimation of fewer array elements and more sources. And the performance is better when the signal-to-noise ratio is low. Based on the traditional DOA estimation algorithm. The signal analysis and processing technology of high-order cumulant in DOA estimation in recent years is studied. The DOA estimation based on Gao Si color noise condition is introduced in detail. In this paper, MUSIC algorithm based on fourth-order cumulant is applied. In order to remove a lot of data redundancy in the algorithm, an improved fourth-order MUSIC algorithm is proposed. The simulation results show that the algorithm is under unknown Gao Si noise. The incident angle of the signal can be estimated accurately, and the higher the order, the better the estimation performance.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN911.23

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本文編號(hào)：1422334