發(fā)布時(shí)間：2018-11-27 19:21

【摘要】：隨著陣列信號DOA估計(jì)與跟蹤技術(shù)在雷達(dá)探測和聲吶定位等實(shí)際場景中的應(yīng)用愈來愈廣泛和深入,人們對DOA估計(jì)與跟蹤技術(shù)的要求也日益提高。近年來,隨著壓縮感知理論的發(fā)展,其對快拍數(shù)要求低和天然的解相干性等鮮明的優(yōu)點(diǎn)促進(jìn)了陣列信號DOA估計(jì)技術(shù)的不斷深入研究;并且,隨著動(dòng)態(tài)壓縮感知等理論的形成和不斷完善,基于壓縮感知理論的DOA跟蹤技術(shù)也取得了一定的研究成果。本文在這一背景下對基于壓縮感知理論的DOA估計(jì)和跟蹤算法進(jìn)行了相關(guān)研究,主要研究內(nèi)容歸納如下:1)通過對平滑l0范數(shù)的研究,采用改進(jìn)后性能更加優(yōu)異的平滑函數(shù)來逼近l0范數(shù),提出一種基于改進(jìn)平滑l0范數(shù)的DOA估計(jì)算法,該算法容易實(shí)現(xiàn)且精度較高,在單快拍條件下就能對DOA進(jìn)行較好的估計(jì),且相比OMP算法和平滑l0范數(shù)原始算法具有更好的性能。2)通過對改進(jìn)平滑l0范數(shù)采用新的加權(quán)方式進(jìn)行處理,提出一種基于加權(quán)平滑l0范數(shù)的DOA估計(jì)算法,該算法同樣容易實(shí)現(xiàn),在單快拍條件下就能實(shí)現(xiàn)較高精度的DOA估計(jì),且相比基于改進(jìn)平滑l0范數(shù)的DOA估計(jì)算法具有更高的估計(jì)精度。3)實(shí)際應(yīng)用中的DOA估計(jì)技術(shù)通常為MMV模型,本文將基于加權(quán)平滑l0范數(shù)的DOA估計(jì)算法推廣到MMV模型下,提出一種基于多快拍加權(quán)平滑l0范數(shù)的DOA估計(jì)算法,該算法在較低快拍數(shù)條件下就可實(shí)現(xiàn)DOA的高精度估計(jì)。4)針對運(yùn)動(dòng)目標(biāo)信號源的DOA跟蹤問題,將動(dòng)態(tài)壓縮感知理論的處理方法應(yīng)用到動(dòng)態(tài)DOA這一時(shí)變稀疏信號中,并建立動(dòng)態(tài)DOA稀疏概率模型以獲得加權(quán)l(xiāng),范數(shù)的權(quán)值,最終通過對線性加權(quán)l(xiāng)1范數(shù)的最小化,提出一種單快拍情況下的動(dòng)態(tài)壓縮感知DOA跟蹤算法,該算法可實(shí)現(xiàn)較高精度的DOA跟蹤,在一定信噪比條件下具有比PASTd算法和粒子濾波算法更好的DOA跟蹤性能。5)為提升動(dòng)態(tài)壓縮感知DOA跟蹤算法對噪聲的抗干擾能力,將該算法推廣到MMV模型下,同時(shí)對接收信號進(jìn)行奇異值分解處理以降低計(jì)算量,最終提出一種多快拍動(dòng)態(tài)壓縮感知DOA跟蹤算法,該算法可以在快拍數(shù)較少且信噪比較低的情況下實(shí)現(xiàn)較高精度的DOA跟蹤。
[Abstract]:With the increasing application of array signal DOA estimation and tracking technology in radar detection and sonar localization, the requirements of DOA estimation and tracking technology are increasing. In recent years, with the development of compression sensing theory, its advantages such as low requirement of rapid-beat number and natural desiccation have promoted the further research of array signal DOA estimation technology. Moreover, with the formation and improvement of the theory of dynamic compression sensing, the DOA tracking technology based on the theory of compressed sensing has also achieved some research results. In this context, the DOA estimation and tracking algorithm based on compressed perception theory is studied in this paper. The main research contents are summarized as follows: 1) through the research of smoothing l0 norm, The improved smoothing function is used to approximate the l0 norm, and a DOA estimation algorithm based on the improved smoothing l0 norm is proposed. The algorithm is easy to implement and has high accuracy. The DOA can be estimated better under the condition of single shot. Compared with the OMP algorithm and the original smoothing l0 norm algorithm, it has better performance. 2) A new DOA estimation algorithm based on the weighted smoothing l0 norm is proposed by using a new weighting method for the improved smoothing l0 norm. This algorithm is also easy to implement, and can achieve high precision DOA estimation under the condition of single beat. Compared with the DOA estimation algorithm based on improved smoothing l0 norm, it has higher estimation accuracy. 3) the DOA estimation technique in practical application is usually MMV model. In this paper, the DOA estimation algorithm based on weighted smoothing l0 norm is extended to MMV model. A new DOA estimation algorithm based on multi-beat weighted smoothing l0 norm is proposed. The algorithm can realize the high precision estimation of DOA under the condition of lower beat number. 4) aiming at the DOA tracking problem of moving target signal source, a new algorithm is proposed. The processing method of dynamic compression sensing theory is applied to the transient sparse signal of dynamic DOA, and the sparse probability model of dynamic DOA is established to obtain the weight of weighted L and norm. Finally, the linear weighted L 1 norm is minimized. This paper presents a dynamic compression sensing DOA tracking algorithm in the case of single racket, which can achieve high precision DOA tracking. Under certain SNR conditions, the DOA tracking performance is better than that of PASTd algorithm and particle filter algorithm. 5) in order to improve the anti-jamming ability of dynamic compression sensing DOA tracking algorithm to noise, the algorithm is extended to MMV model. At the same time, the received signal is processed by singular value decomposition to reduce the computational complexity. Finally, a multi-beat dynamic compression sensing DOA tracking algorithm is proposed, which can achieve high precision DOA tracking under the condition of fewer beats and lower signal-to-noise ratio (SNR).
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN911.23

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