本文選題：寬帶信號(hào)　切入點(diǎn)：DOA估計(jì)　出處：《南京大學(xué)》2017年碩士論文

【摘要】：陣列信號(hào)處理技術(shù)的應(yīng)用涉及廣泛,在軍事及國(guó)民經(jīng)濟(jì)領(lǐng)域均有重大發(fā)展。作為陣列信號(hào)處理的重要分支,波達(dá)方向(Direction of Arriva1,DOA)估計(jì)已成為熱門研究課題。目前關(guān)于窄帶信號(hào)空間測(cè)向的算法已趨于成熟,而對(duì)于攜帶更多有效信息、具有更高應(yīng)用價(jià)值的寬帶信號(hào),傳統(tǒng)的窄帶信號(hào)算法對(duì)其并不適用,需要研究新的適用于寬帶信號(hào)的高分辨DOA估計(jì)算法。本文重點(diǎn)研究寬帶信號(hào)的高分辨DOA估計(jì)算法,研究?jī)?nèi)容包括:1.對(duì)傳感器構(gòu)成的陣列進(jìn)行理想化假設(shè),分別對(duì)寬帶及窄帶信號(hào)構(gòu)建信號(hào)模型。研究經(jīng)典窄帶高分辨測(cè)向算法,通過實(shí)驗(yàn)仿真分析陣列信號(hào)模型各類參數(shù)對(duì)MUSIC、ESPRIT算法估計(jì)精度的影響,該方法可用于基于子帶的寬帶DOA估計(jì)。2.分析空間平滑技術(shù)實(shí)現(xiàn)信號(hào)解相干時(shí)所能達(dá)到的信源數(shù)上限,研究基于矩陣共軛重構(gòu)實(shí)現(xiàn)信號(hào)解相干的修正MUSIC算法。進(jìn)行了實(shí)驗(yàn)仿真,分析前向平滑、前后向平滑以及修正MUSIC三種算法的性能。3.分析了處理寬帶信號(hào)的非相干子空間算法(ISM),并基于修正MUSIC改進(jìn)ISM算法,彌補(bǔ)其無法解相干的缺陷。鑒于相關(guān)子空間算法(CSM)構(gòu)造的聚焦矩陣并不是唯一的,分別研究以陣列流型及去噪后的接收數(shù)據(jù)為基準(zhǔn)的RSS、TCT算法,通過仿真對(duì)比兩類算法在不同信噪比下所表現(xiàn)的性能差異。4.傳統(tǒng)MUSIC算法的統(tǒng)計(jì)特性是建立在陣元數(shù)固定、采集的樣本數(shù)趨于正無窮的基礎(chǔ)上的。在實(shí)際應(yīng)用中,陣列的陣元數(shù)較大,受硬件限制,陣列采集的樣本數(shù)有限,無法滿足快拍數(shù)遠(yuǎn)大于陣元數(shù)的條件。當(dāng)樣本數(shù)較小時(shí),MUSIC算法的估計(jì)精度會(huì)出現(xiàn)較大偏差。本文提出一種改進(jìn)MUSIC算法,在采集的樣本數(shù)有限的情況下,通過改進(jìn)接收的離散數(shù)據(jù)所分解的信號(hào)子空間,提高DOA的估計(jì)精度。對(duì)CSM聚焦后的頻域窄帶模型數(shù)據(jù)采用本文改進(jìn)算法進(jìn)行了實(shí)驗(yàn)仿真,結(jié)果表明改進(jìn)的CSM具有更高的估計(jì)精度。
[Abstract]:Array signal processing technology has been widely used in military and national economy. As an important branch of array signal processing, Direction of arrival (DOA) estimation has become a hot research topic. At present, the algorithm of direction finding for narrowband signals has become mature, while for wideband signals with more effective information, it has higher application value. The traditional narrowband signal algorithm is not suitable for it, so it is necessary to study a new high-resolution DOA estimation algorithm for wideband signals. This paper focuses on the high-resolution DOA estimation algorithm for wideband signals. The research contents include: 1.The ideal assumption of the sensor array is given, and the signal models of wideband and narrowband signals are constructed, respectively, and the classical narrowband high-resolution direction-finding algorithm is studied. The influence of various parameters of array signal model on the estimation accuracy of MUSICI Esprit algorithm is analyzed by experimental simulation. The method can be used to estimate wideband DOA based on subband. 2. The upper limit of source number can be obtained when spatial smoothing technology is used to realize signal decoherence. The modified MUSIC algorithm based on matrix conjugate reconstruction to realize signal decoherence is studied. The experimental simulation is carried out and the forward smoothing is analyzed. The performance of three algorithms, forward smoothing and modified MUSIC. 3. The incoherent subspace algorithm for wideband signal processing is analyzed, and the modified ISM algorithm is improved based on modified MUSIC. In view of the fact that the focusing matrix constructed by the correlation subspace algorithm (CSM) is not unique, the RSS-TCT algorithm based on the array flow pattern and the de-noised received data is studied respectively. The statistical characteristics of the traditional MUSIC algorithm are based on the fixed number of array elements, and the number of samples collected tends to be infinitely positive. The array has a large number of elements and is limited by hardware, so the number of samples collected by the array is limited. It is impossible to satisfy the condition that the number of beats is far larger than the number of elements of the matrix. When the number of samples is small, there will be a large deviation in the estimation accuracy of music algorithm. In this paper, an improved MUSIC algorithm is proposed, in which the number of samples collected is limited. The estimation accuracy of DOA is improved by improving the signal subspace decomposed by the received discrete data. The experimental simulation of the CSM focused narrow-band model data in frequency domain is carried out by using the improved algorithm in this paper. The results show that the improved CSM has higher estimation accuracy.
【學(xué)位授予單位】：南京大學(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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本文編號(hào)：1664363