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DOA estimation of the moving targets in shallow water based on vector optimization beamforming and normal-mode theory

机译:基于矢量优化波束形成和正模理论的浅水运动目标DOA估计

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摘要

DOA estimation is one of the most important tasks for sonar system. However, the performance of conventional high-resolution DOA estimation methods is influenced because of the neglect of some important factors, such as effect of underwater sound channel, the array position errors and so on. In order to improve the robustness of the high-resolution DOA estimation methods, the vector optimization robust beamforming method is realized by adding a strong joint constraint to the weight vector norm and the steering vector errors. In addition, simulating the matched-field processing method, the DOA estimation of underwater moving targets can be computed by combining adaptive robust beamforming and normal-mode theory. It is shown that the adaptive beamforming which is presented in this paper has higher peak to maximum sidelobe ratio (PSR) and narrower ∼3dB beamwidth.
机译:DOA估计是声纳系统最重要的任务之一。然而,由于忽略了一些重要因素,如水下声通道的影响,阵列位置误差等,影响了传统高分辨率DOA估计方法的性能。为了提高高分辨率DOA估计方法的鲁棒性,向量优化鲁棒波束形成方法是通过对权重向量范数和操纵向量误差添加强联合约束来实现的。此外,通过模拟匹配场处理方法,可以通过将自适应鲁棒波束成形和正常模式理论相结合来计算水下运动目标的DOA估计。结果表明,本文提出的自适应波束形成具有较高的峰峰值与最大旁瓣比(PSR)和较窄的〜3dB波束宽度。

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