發(fā)布時(shí)間：2018-05-08 05:13

  本文選題：陣列信號(hào)處理 + 寬帶信號(hào)處理��； 參考：《哈爾濱工程大學(xué)》2014年碩士論文

【摘要】：隨著信號(hào)復(fù)雜度的增加,對(duì)寬帶信號(hào)的處理成為學(xué)術(shù)領(lǐng)域中一個(gè)重要研究方向。其中寬帶信號(hào)的陣列信號(hào)處理是信號(hào)處理的一個(gè)重要分支。寬帶信號(hào)源的波達(dá)方向估計(jì)(DOA估計(jì))技術(shù)廣泛應(yīng)用于通信、雷達(dá)、聲吶等軍用和民用領(lǐng)域。本文采用均勻圓陣和均勻線陣作為接收陣列,對(duì)寬帶信號(hào)的DOA估計(jì)問(wèn)題進(jìn)行了深入的研究。論文的主要工作包括:1.建立了窄帶陣列信號(hào)、寬帶陣列信號(hào)及相關(guān)陣列信號(hào)的數(shù)學(xué)模型,并對(duì)兩種基于子空間分解的DOA估計(jì)算法,多重信號(hào)分類(MUSIC)算法和旋轉(zhuǎn)不變子空間(ESPRIT)算法進(jìn)行了研究。MUSIC算法的核心思想,是利用噪聲子空間和信號(hào)子空間之間的正交特性完成信號(hào)源入射角度的估計(jì)。ESPRIT算法則是利用兩個(gè)相同子陣間的旋轉(zhuǎn)不變性來(lái)估計(jì)信源入射角度。計(jì)算機(jī)仿真驗(yàn)證了兩種算法的性能。2.設(shè)計(jì)了寬帶陣列信號(hào)DOA估計(jì)的方案,并對(duì)相關(guān)算法進(jìn)行了研究。寬帶DOA估計(jì)算法利用聚焦變換和窄帶信號(hào)信源數(shù)目估計(jì)算法完成了寬帶信號(hào)DOA估計(jì)。論文詳細(xì)論述和分析了 TCT聚焦和RSS聚焦矩陣的構(gòu)造依據(jù)和方法。對(duì)于子空間分解需要已知信源數(shù)目的問(wèn)題,應(yīng)用蓋氏圓方法和信息論方法估計(jì)信源數(shù)目,進(jìn)而完成信號(hào)子空間和噪聲子空間的分解。計(jì)算機(jī)仿真驗(yàn)證了算法的性能和可行性。3.信源數(shù)目估計(jì)誤差會(huì)直接影響子空間類DOA估計(jì)算法的性能。為了解決這個(gè)問(wèn)題,本文在寬帶陣列信號(hào)處理基礎(chǔ)上,提出了一種未知信源數(shù)目的寬帶DOA估計(jì)方法。算法依據(jù)波束形成算法理論,通過(guò)加權(quán)向量的選擇并依據(jù)陣列輸出來(lái)估計(jì)波達(dá)方向,消除了信源數(shù)目估計(jì)誤差對(duì)DOA估計(jì)性能的影響。仿真結(jié)果表明,寬帶未知信源數(shù)目估計(jì)算法具有較高的估計(jì)性能,而且對(duì)于空間信源的信噪比具有一定的魯棒性。
[Abstract]:With the increase of signal complexity, broadband signal processing has become an important research direction in academic field. The array signal processing of wideband signal is an important branch of signal processing. DOA estimation of wideband signal sources (DOA estimation) is widely used in military and civil fields such as communication radar sonar and so on. In this paper, uniform circular array and uniform linear array are used as receiving arrays, and the problem of DOA estimation for wideband signals is studied in depth. The main work of the thesis includes 1: 1. The mathematical models of narrowband array signal, wideband array signal and correlation array signal are established, and two DOA estimation algorithms based on subspace decomposition are proposed. In this paper, the core idea of the multiplex signal classification algorithm (MUSIC) and the rotation-invariant subspace Esprit algorithm is studied. The Esprit algorithm uses the orthogonal characteristic between the noise subspace and the signal subspace to estimate the incident angle of the signal source. The Esprit algorithm uses the rotation invariance between two identical subarrays to estimate the source incident angle. The performance of the two algorithms is verified by computer simulation. The scheme of DOA estimation for wideband array signal is designed, and the related algorithms are studied. Wideband DOA estimation algorithm uses focusing transform and narrowband signal source number estimation algorithm to complete wideband signal DOA estimation. In this paper, the construction basis and method of TCT focusing and RSS focusing matrix are discussed and analyzed in detail. For the problem that the number of information sources is needed for subspace decomposition, the number of sources is estimated by using the Ghaehler circle method and the information theory method, and then the signal subspace and noise subspace are decomposed. The performance and feasibility of the algorithm are verified by computer simulation. The error of source number estimation will directly affect the performance of subspace-like DOA estimation algorithm. To solve this problem, a wideband DOA estimation method with unknown number of sources is proposed based on wideband array signal processing. Based on the theory of beamforming algorithm, the estimation of DOA is based on the selection of weighted vectors and the array output, which eliminates the influence of the estimation error of the number of sources on the performance of DOA estimation. Simulation results show that the wideband unknown source number estimation algorithm has high estimation performance and is robust to the signal-to-noise ratio of spatial sources.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.7

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本文編號(hào)：1860090