本文選題：魯棒自適應(yīng)波束形成 + 不確定集��； 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：在陣列信號處理中,自適應(yīng)波束形成技術(shù)是普遍要考慮的任務(wù)并具有廣泛的應(yīng)用。依賴于數(shù)據(jù)的傳統(tǒng)波束形成算法能維持感興趣信號的幅度響應(yīng)為1并抑制干擾。但是在實(shí)際應(yīng)用場景中,由于陣列和傳播環(huán)境存在非理想性,傳統(tǒng)波束形成技術(shù)的性能會嚴(yán)重下降。其原因在于感興趣目標(biāo)被當(dāng)做干擾而受到抑制。很多魯棒自適應(yīng)波束形成技術(shù)被提出來以增加波束形成器的魯棒性。在這些技術(shù)中,對角加載是一種很流行的魯棒算法。對角加載技術(shù)在Capon波束形成器的目標(biāo)函數(shù)中增加了權(quán)值向量的范數(shù)約束。本質(zhì)上,對角加載技術(shù)相對于在輸入端注入人工白噪聲以降低輸入信噪比。這樣能夠降低波束形成器對導(dǎo)向矢量誤差的敏感性。為了克服傳統(tǒng)對角加載算法的缺點(diǎn),很多文獻(xiàn)考慮導(dǎo)向矢量的不確定集以便明確計(jì)算對角加載算法中的加載量。在本論文中,主要有以下三個貢獻(xiàn):(1)我們證明了不確定集中的幅度響應(yīng)波動約束條件可以轉(zhuǎn)變?yōu)闄?quán)值向量的范數(shù)約束,其中權(quán)值向量范數(shù)的最大值跟不確定集的大小和陣元數(shù)目有關(guān)。(2)為了抑制干擾,我們提出了一種新的魯棒線性約束最小方差算法,其可以看做是將線性約束最小方差和范數(shù)約束Capon算法結(jié)合起來。同時我們推導(dǎo)出與這種算法對應(yīng)最優(yōu)化問題的閉式解。(3)當(dāng)我們無法獲得干擾的方向信息時,我們提出了一種使用旁瓣抑制的魯棒算法。在合理選擇參數(shù)的前提下,可以使用CVX軟件包求解相應(yīng)的最優(yōu)化問題。我們將論文中提出的算法跟其他魯棒自適應(yīng)波束形成算法進(jìn)行了對比。在相同場景中,仿真結(jié)果表明論文所提出算法比其他測試算法具有更強(qiáng)的魯棒性。
[Abstract]:In array signal processing, adaptive beamforming technology is a common task to be considered and has a wide range of applications. The traditional beamforming algorithm based on data can maintain the amplitude response of the signal of interest to 1 and suppress interference. However, in practical applications, the performance of traditional beamforming technology will be seriously degraded due to the non-ideal array and propagation environment. The reason is that the object of interest is suppressed as interference. Many robust adaptive beamforming techniques have been proposed to increase the robustness of beamforming. Among these techniques, diagonal loading is a popular robust algorithm. The diagonal loading technique adds the norm constraint of the weight vector to the objective function of the Capon beamformer. In essence, diagonal loading technique is relative to injecting artificial white noise into the input to reduce the input signal to noise ratio (SNR). This can reduce the sensitivity of beamformer to steering vector error. In order to overcome the shortcomings of the traditional diagonal loading algorithm, many literatures consider the uncertain set of the guidance vector in order to calculate the loading quantity in the diagonal loading algorithm. In this paper, there are three main contributions: 1) We prove that the fluctuation constraints of amplitude response in uncertain sets can be transformed into norm constraints of weight vectors. Where the maximum value vector norm is related to the size of the uncertain set and the number of matrix elements. In order to suppress interference, we propose a new robust linear constrained minimum variance algorithm. It can be seen as a combination of linear constraint minimum variance and norm constrained Capon algorithm. At the same time, we derive the closed solution of the optimization problem corresponding to this algorithm. When we can not obtain the direction information of the interference, we propose a robust algorithm using sidelobe suppression. On the premise of reasonable selection of parameters, CVX software package can be used to solve the corresponding optimization problem. We compare the proposed algorithm with other robust adaptive beamforming algorithms. In the same scenario, the simulation results show that the proposed algorithm is more robust than other test algorithms.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN911.7

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