基于不确定集响应波动约束的鲁棒波束形成技术

发布时间：2018-04-25 09:27

本文选题：鲁棒自适应波束形成 + 不确定集　；参考：《电子科技大学》2014年硕士论文

【摘要】：在阵列信号处理中,自适应波束形成技术是普遍要考虑的任务并具有广泛的应用。依赖于数据的传统波束形成算法能维持感兴趣信号的幅度响应为1并抑制干扰。但是在实际应用场景中,由于阵列和传播环境存在非理想性,传统波束形成技术的性能会严重下降。其原因在于感兴趣目标被当做干扰而受到抑制。很多鲁棒自适应波束形成技术被提出来以增加波束形成器的鲁棒性。在这些技术中,对角加载是一种很流行的鲁棒算法。对角加载技术在Capon波束形成器的目标函数中增加了权值向量的范数约束。本质上,对角加载技术相对于在输入端注入人工白噪声以降低输入信噪比。这样能够降低波束形成器对导向矢量误差的敏感性。为了克服传统对角加载算法的缺点,很多文献考虑导向矢量的不确定集以便明确计算对角加载算法中的加载量。在本论文中,主要有以下三个贡献:(1)我们证明了不确定集中的幅度响应波动约束条件可以转变为权值向量的范数约束,其中权值向量范数的最大值跟不确定集的大小和阵元数目有关。(2)为了抑制干扰,我们提出了一种新的鲁棒线性约束最小方差算法,其可以看做是将线性约束最小方差和范数约束Capon算法结合起来。同时我们推导出与这种算法对应最优化问题的闭式解。(3)当我们无法获得干扰的方向信息时,我们提出了一种使用旁瓣抑制的鲁棒算法。在合理选择参数的前提下,可以使用CVX软件包求解相应的最优化问题。我们将论文中提出的算法跟其他鲁棒自适应波束形成算法进行了对比。在相同场景中,仿真结果表明论文所提出算法比其他测试算法具有更强的鲁棒性。
[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.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.7

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