本文選題：陣列信號(hào)處理 + DOA估計(jì)�。� 參考：《西北工業(yè)大學(xué)》2016年博士論文

【摘要】：被動(dòng)多目標(biāo)分辨與方位估計(jì)技術(shù)研究在聲納、雷達(dá)、海洋探測等領(lǐng)域中有著非常重要的地位。論文系統(tǒng)研究了被動(dòng)多目標(biāo)分辨與方位估計(jì)的關(guān)鍵技術(shù),主要研究內(nèi)容包括:1.建立了DOA估計(jì)的陣列模型,對(duì)經(jīng)典的窄帶高分辨子空間算法進(jìn)行了分析,研究了常用的解相干方法及快速子空間算法,并對(duì)其進(jìn)行了仿真驗(yàn)證。針對(duì)窄帶準(zhǔn)平穩(wěn)信號(hào)下KR-MUSIC算法運(yùn)算量大且需要信源先驗(yàn)信息的問題,提出了無需信源數(shù)目的低復(fù)雜度算法,該方法利用信號(hào)的分段平穩(wěn)性、結(jié)合Khatri-Rao積虛擬增加了陣列孔徑。通過正交補(bǔ)算子可降低噪聲的影響,利用循環(huán)移位矩陣降低了陣列方向矢量的維數(shù),提高了算法的運(yùn)行速度,結(jié)合全加權(quán)MUSIC理論實(shí)現(xiàn)了無需信源先驗(yàn)信息的準(zhǔn)平穩(wěn)信號(hào)DOA估計(jì)。實(shí)驗(yàn)仿真展示了該方法能估計(jì)的信源數(shù)超過了陣元數(shù)目,且具有較高的估計(jì)精度。2.研究了寬帶非相干信號(hào)子空間法(ISSM:Incoherent Signal Subspace Method)及相干信號(hào)子空間法(CSSM:Coherent Signal Subspace Method),分析了它們的測向原理,對(duì)典型的聚焦類算法RSS及TCT進(jìn)行了研究,通過仿真驗(yàn)證了算法的有效性。分析了寬帶投影子空間正交性測試算法(TOPS:Test of Orthogonality of Projected Subspace)和頻域子空間正交性測試算法(TOFS:Test of Orthogonality of Frequency Subspace)�；趯�(duì)稱譜理論,提出了一種新的寬帶相干信號(hào)快速DOA估計(jì)算法,該方法利用Toeplitz矩陣重構(gòu),可實(shí)現(xiàn)不損失陣列孔徑的信號(hào)解相干,結(jié)合實(shí)值轉(zhuǎn)換將復(fù)矩陣映射為實(shí)矩陣,降低了子空間分解的運(yùn)算量,利用噪聲子空間及其共軛重新構(gòu)造空間譜,根據(jù)譜對(duì)稱性,在半譜內(nèi)搜索即可得到信號(hào)的方位角。仿真結(jié)果表明該算法能處理寬帶相干源,運(yùn)算量小且具有較小的估計(jì)誤差。3.研究了NC-MUSIC、實(shí)值NC-MUSIC、EPM等非圓信號(hào)DOA估計(jì)算法并進(jìn)行了仿真驗(yàn)證。分析了非圓信號(hào)和圓信號(hào)共存下的MUSIC算法、ESPRIT算法及酉ESPRIT算法,信號(hào)共存下,信號(hào)子空間維數(shù)得到了擴(kuò)展,可以分辨更多的信號(hào),在信源過載下算法有效。針對(duì)非圓信號(hào)和圓信號(hào)共存下MUSIC算法運(yùn)算量較大的問題,提出了一種快速算法,該方法將實(shí)值轉(zhuǎn)換和多級(jí)維納濾波技術(shù)應(yīng)用到信號(hào)共存下,降低了該情形下MUSIC算法的運(yùn)算量,利用譜峰中圓信號(hào)角度會(huì)重復(fù)出現(xiàn)而非圓信號(hào)角度只會(huì)出現(xiàn)一次的規(guī)律,可以準(zhǔn)確區(qū)分圓與非圓信號(hào)。仿真結(jié)果驗(yàn)證了算法的有效性。4.研究了窄帶不相關(guān)和相干信號(hào)混合下的DOA估計(jì)算法,對(duì)空間差分矩陣平方算法和空間差分矩陣特征分解算法進(jìn)行了理論分析和實(shí)驗(yàn)仿真。為提高低信噪比下算法分辨的成功概率,提出了空間差分Mini-Norm算法,所提算法在不相關(guān)和相干信號(hào)的DOA估計(jì)中采用的都是Mini-Norm方法,算法分辨率高、對(duì)參數(shù)變化不敏感,仿真驗(yàn)證了新算法具有良好的性能。針對(duì)空間差分矩陣平方算法運(yùn)算量大且解相干會(huì)帶來陣元損失的問題,給出了一種改進(jìn)算法,該方法利用新空間差分技術(shù),解相干的陣元損失較傳統(tǒng)的空間平滑要小,結(jié)合實(shí)值轉(zhuǎn)換及線性傳播算子理論,可快速獲得相干信號(hào)的噪聲子空間。計(jì)算機(jī)仿真實(shí)驗(yàn)表明所提算法估計(jì)精度較高且具有較低的計(jì)算復(fù)雜度。5.利用實(shí)值轉(zhuǎn)換及空間差分技術(shù),結(jié)合TOFS算法理論,發(fā)展了寬帶不相關(guān)信號(hào)和相干信號(hào)混合下的DOA估計(jì)算法,該算法利用寬帶信號(hào)各個(gè)頻點(diǎn)協(xié)方差矩陣的厄米特性,通過酉轉(zhuǎn)換可實(shí)現(xiàn)該頻點(diǎn)復(fù)矩陣的實(shí)值化,通過實(shí)值化的TOFS法能迅速實(shí)現(xiàn)不相關(guān)信號(hào)的DOA估計(jì)。利用空間差分及Toeplitz化技術(shù),通過實(shí)值TOFS算法,在不降低陣列孔徑的條件下,可快速獲得相干信號(hào)的DOA估計(jì)。仿真結(jié)果表明新算法能同時(shí)估計(jì)寬帶不相關(guān)和相干信源,在信源數(shù)目大于陣元數(shù)目的情形下DOA估計(jì)有效,且具有較低的運(yùn)算量。
[Abstract]:The research of passive multi-target resolution and azimuth estimation technology plays a very important role in sonar, radar, ocean detection and other fields. This paper systematically studies the key technologies of passive multi-target resolution and azimuth estimation. The main research contents include: 1. the array model of DOA estimation is established, and the classical narrowband high resolution subspace algorithm is carried out. In this paper, the common method of decoherence and fast subspace algorithm are studied, and the simulation verification is carried out. In view of the problem that the KR-MUSIC algorithm is large and needs the prior information of the source under the narrow band quasi stationary signal, a low complexity algorithm without the number of sources is proposed. This method uses the piecewise stability of the signal and combines with the Khatri-Rao. Through the orthogonal complement operator, the effect of the noise is reduced. The dimension of the array direction vector is reduced by the cyclic shift matrix, and the speed of the algorithm is improved. The quasi stationary signal DOA estimation without the prior information of the source is realized with the full weighted MUSIC theory. The experimental simulation shows that the method can be estimated. The number of sources exceeds the number of elements, and has a high estimation precision..2. studies the ISSM:Incoherent Signal Subspace Method (Method) and the coherent signal subspace (CSSM:Coherent Signal Subspace Method). The principle of their direction finding is analyzed, and the typical focusing algorithm RSS and TCT are studied. The effectiveness of the algorithm is verified by over simulation. The TOPS:Test of Orthogonality of Projected Subspace and the frequency domain subspace orthogonality testing algorithm (TOFS:Test of Orthogonality of Frequency Subspace) are analyzed. Based on the symmetric spectrum theory, a new broadband coherent signal is proposed. The algorithm uses the Toeplitz matrix reconstruction to realize the signal decoherence without loss of the array aperture. The complex matrix is mapped into a real matrix by the real value conversion. The computation of the subspace decomposition is reduced. The spatial spectrum is reconstructed by the noise subspace and its conjugate. According to the spectral symmetry, the signal can be obtained in the semi spectrum. The simulation results show that the algorithm can deal with wideband coherent sources with small computation and smaller estimation error.3.. The NC-MUSIC, real NC-MUSIC, EPM and other non circular signal DOA estimation algorithms are simulated and verified. The MUSIC algorithm, ESPRIT algorithm and unitary ESPRIT algorithm, and the coexistence of signal, are analyzed in the presence of non circular signals and circular signals. At the same time, the dimension of the signal subspace is extended to distinguish more signals, and the algorithm is effective under the source overload. A fast algorithm is proposed for the problem of the large amount of operation of MUSIC algorithm under the coexistence of non circular signals and circular signals. This method applies the real value conversion and multilevel Wiener filtering technique to the coexistence of signals and reduces the situation. The calculation of the next MUSIC algorithm, using the angle of the circular signal in the spectral peak and the angle of the circular signal, only one time, can distinguish between the circle and the non circular signal. The simulation results verify the effectiveness of the algorithm.4. and study the DOA estimation algorithm of the mixture of narrowband unrelated and coherent signals, and the square calculation of the spatial difference matrix. In order to improve the success probability of algorithm resolution under low signal to noise ratio, a spatial difference Mini-Norm algorithm is proposed. The proposed algorithm used in the DOA estimation of unrelated and coherent signals is all Mini-Norm square method. The algorithm has high resolution and is insensitive to the change of parameters. The simulation proves that the new algorithm has good performance. An improved algorithm is given for the problem that the space difference matrix square algorithm is large and coherent will cause the loss of the array element. This method uses the new space difference technique, and the loss of the decoherence array element is smaller than the traditional space smoothing, and combines the real value conversion and the linear propagator theory. On the other hand, the noise subspace of coherent signals can be quickly obtained. Computer simulation experiments show that the proposed algorithm has high estimation accuracy and low computational complexity.5. using real value conversion and spatial difference technology. Combined with the theory of TOFS algorithm, the DOA estimation algorithm with wide band uncorrelated signal and coherent signal is developed. The real value of the complex matrix of the frequency point can be realized by the unitary transformation, and the DOA estimation of the uncorrelated signals can be realized quickly through the unitary transformation. By using the spatial difference and the Toeplitz technology, the coherent signal can be quickly obtained without reducing the aperture of the array with the real value TOFS algorithm. The simulation results show that the new algorithm can simultaneously estimate the wideband uncorrelated and coherent sources, and the DOA estimation is effective in the case of the number of sources greater than the number of elements, and has a lower computation.

【學(xué)位授予單位】：西北工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TN911.7

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