一种新的替代对角加载的鲁棒自适应波束形成方法

S. Sirianunpiboon
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引用次数: 0

摘要

斜向加载是提高优化波束形成器鲁棒性的有效方法。然而,必须正确选择对角线加载值来实现这一点。本文提出了一种贝叶斯波束形成器,用于处理阵列结构和源到达方向的不确定性。然后,我们介绍了一种不需要对角加载而形成坚固的波束成形的方法。此外,当使用对角线加载时,我们给出了一种简单有效的技术来确定一个良好的加载值。仿真和实验结果表明,两种技术在模拟和实际数据上都具有相似的性能。在本文中,我们提出了一些想法。我们简要地提出了一种贝叶斯方法来处理阵列配置和源方位的不确定性。我们表明,当该方法应用于DOA不确定性时,我们得到了一个与(4)的分布式源问题相同的功率最小化问题。然后我们提出了一种无需对角加载即可从该问题中提取鲁棒波束形成器的方法。这是本文的主要成果。最后,为了进行比较,我们简要介绍了我们开发的一种基于迭代功率估计的最小功率无失真响应(MPDR)波束形成器的对角线加载值确定方法。本文的组织结构如下。在第2节中,我们简要回顾了最小功率波束形成和使这种波束形成器对模型失配具有鲁棒性的基本方法。第3节介绍了具有预期响应约束(ERC)的贝叶斯波束形成。在第4节中,我们提出了这个问题的近似解决方案,避免了对角加载的需要。我们将这种技术与我们开发的一种基于迭代功率估计确定对角加载值的新方法进行了比较;第5节对该技术进行了总结。第6节给出了模拟和实验结果的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel alternative to diagonal loading for robust adaptive beamforming
Diagonal loading has proved an effective way to improve the robustness of the optimum beamformer. However, the diagonal loading value must be properly chosen to achieve this. In this paper we propose a Bayesian beamformer for dealing with uncertainty in array configuration and source direction of arrival. We then introduce a method for forming robust beamfomers without the need for diag- onal loading. Furthermore, when diagonal loading is used we give a simple and effective technique for determining a good value for the loading. Simulations and experimental results show that both techniques exhibit similar perfor- mance on simulated and real data. In this paper we develop a number of ideas. We briefly present a Bayesian method for dealing with uncertainity in array configurations and source DOA. We show that when this method is applied to DOA uncertainty we ob- tain a power minimisation problem which is identical to the distributed source problem of (4). We then present a method for extracting robust beamformers from this prob- lem without the need for diagonal loading. This is the main result of this paper. Finally, for comparison, we briefly present a new method we have developed for de- termining diagonal loading values for the minimum power distortionless response (MPDR) beamformer, based on an iterative power estimate. The paper is organised as follows. In Section 2 we briefly review minimum power beamforming and the ba- sic approaches to making such beamformers robust to model mismatch. Section 3 introduces Bayesian beamforming with expected response constraints (ERC). In Section 4 we propose an approximate solution to this problem which avoids the need for diagonal loading. We compare this technique with a new method we have developed for de- termining diagonal loading values based on an iterative power estimate; this techique is summarised in Section 5. A comparison using both simulation and experimental re- sults is shown in Section 6.
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