| 摘要: |
| 针对机场终端区域复杂环境下IID样本不足，导致极化空时自适应处理（PSTAP）低空湍流检测精度下降的问题，本文提出了一种基于M-SBL-PSTAP的低空湍流检测方法。该方法首先通过稀疏贝叶斯学习迭代估计不同极化通道的杂波稀疏系数矩阵，并在此基础上完成杂波协方差矩阵的估计；随后，在极化-空-时域构建极化空时处理器，实现对杂波的抑制及目标回波的匹配滤波；最后，通过计算湍流信号的速度谱宽及涡旋耗散率，实现对低空湍流的检测。仿真实验结果表明，该方法能够在复杂机场终端区域环境下有效检测低空湍流信号。 |
| 关键词: 机载双极化气象雷达 极化空时自适应处理 低空湍流 复杂环境 |
| DOI：DOI:10.3969/j.issn.1672-2337.2026.03.011 |
| 分类号:TN959.4 |
| 基金项目:国家自然科学基金（624B2046） |
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| Low-Altitude Turbulence Detection Based on M-SBL-PSTAP |
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GUO Jingrui， LI Hai， AI Xiaojian ， LI Shuangshuang， FAN Qingbin
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1. Guilin Changhai Development Co., Ltd., Guilin 541001, China;2. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;3. Inner Mongolia Sub-Bureau, North China Regional Air Traffic Management Bureau of CAAC，Hohhot 010010, China;4. Sichuan Branch, Commercial Aircraft Corporation of China, Ltd., Chengdu 610200, China
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| Abstract: |
| Aiming at the problem of insufficient IID samples in the complex environment of airport terminal areas, which leads to degraded accuracy of low-altitude turbulence detection using polarization space-time adaptive processing（PSTAP）, this paper proposes a low-altitude turbulence detection method based on M-SBL-PSTAP. Firstly, the method employs sparse Bayesian learning to iteratively estimate the clutter sparse coefficient matrix across different polarization channels, thereby enabling accurate estimation of the clutter covariance matrix on this basis. Then, the polarimetric space-time processor is constructed in the polarization-space-time domain to achieve efficient clutter suppression and matched filtering of target echoes. Finally, the velocity spectral width and eddy dissipation rate of the turbulence signal are computed to realize accurate detection of low-altitude turbulence. Simulation results demonstrate that the proposed method can effectively detect low-altitude turbulence signals in the complex airport terminal environment. |
| Key words: airborne dual-polarization weather radar polarization space-time adaptive processing low-altitude turbulence complex environment |
