Noise-interference suppression and data-processing acceleration are crucial to aeroacoustic measurements with phased array in wind tunnels. In this paper, we develop a “multi-window” beamforming algorithm that recursively processes data based on an array-acquisition model. This spatial filtering algorithm is derived from the Kalman filter theory for signal processing. The simulated results show that by using recursive operations, accurate signal estimation is acquired with incoherent and coherent background noise removed in the presence of both channel noise and phase noise. The convergence rate of this recursive algorithm is faster than the existing algorithms. As a result, considerable storage space and computational resources are saved, while testing defects in wind tunnel measurement are revealed and corrected immediately on-site. It has a great potential for real-time localization of sound sources in a noisy environment.

中文翻译：

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风洞中气动声学相控阵测量的递归方法

噪声干扰抑制和数据处理加速对于风洞中相控阵的气动声学测量至关重要。在本文中，我们开发了一种“多窗口”波束成形算法，该算法基于阵列采集模型递归处理数据。这种空间滤波算法源自用于信号处理的卡尔曼滤波器理论。仿真结果表明，在信道噪声和相位噪声都存在的情况下，通过使用递归运算，可以在去除非相干和相干背景噪声的情况下获得准确的信号估计。这种递归算法的收敛速度比现有算法快。结果，节省了可观的存储空间和计算资源，同时在现场立即发现和纠正风洞测量中的测试缺陷。