Multistage 2D DoA Estimation in Low SNR
Multistage 2D DoA Estimation in Low SNR
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DOI：
10.1109/icc45041.2023.10279283
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Xue Wei;D. Saha;Gregory Hellbourg;Aveek Dutta
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文献类型：
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作者：
Xue Wei;D. Saha;Gregory Hellbourg;Aveek Dutta
到达方向（DoA）估计在各种应用中具有重要的作用，在现代通信中得到了广泛的应用，在现代通信中，信号功率大于噪声功率才能进行解码。现有的方法在低信噪比（SNR）下的精度不如在高信噪比下的精度。然而，射电天文学或遥感等被动传感在极低的信噪比下工作，其中来自通信系统的最弱射频干扰（RFI）会损害科学观测。因此，有必要估计低信噪比下RFI的DoA，以便在望远镜或辐射计上消除它。在本文中，我们提出了一种三阶段算法，该算法系统地利用数字波束形成，创建虚拟子阵列，检查多个选项并引入聚类来估计低信噪比下的DoA。该算法在加性高斯白噪声（AWGN）和多径衰落信道中的正弦信号和广播自动相关监视（ADS-B）信号中进行了仿真。实验结果表明，该方法在低信噪比下优于MUSIC （MUltiple SIgnal Classification）算法。
Direction of arrival (DoA) estimation has an important role in various applications and is widely used in modern communication, where signal power is higher than noise power for it to be decoded. Existing methods do not perform as accurately in low signal to noise ratio (SNR) as they do in higher SNR. However, passive sensing like radio astronomy or remote sensing operates at extremely low SNR, where the weakest radio frequency interference (RFI) from communication system impairs the scientific observations. Hence, it is essential to estimate the DoA of RFI at low SNR so that it can be removed at the telescopes or radiometers. In this paper, we propose a three stage algorithm that methodically exploits digital beamforming, creates virtual subarrays, inspects multiple options and introduces clustering to estimate the DoA in low SNRs. The proposed algorithm is simulated with sinusoidal as well as Automatic Dependent Surveillance-Broadcast (ADS-B) signals in Additive White Gaussian Noise (AWGN) and multipath fading channels. Experimental results show the proposed method outperforms well-known MUSIC (MUltiple SIgnal Classification) algorithm in low SNR.