便携式高频雷达方向图校准及数据质量控制研究

doi:10.3969/j.issn.1000-5641.2025.06.014

摘要/Abstract

摘要：

高频地波雷达因覆盖范围广、分辨率高、全天候观测能力强, 在海洋流场监测和预报应用中潜力巨大. 针对其数据处理链中的两个关键步骤, 构建了结合无人机天线方向图校准与多算法检测异常值的优化方案. 通过无人机搭载信标与GPS (Global Positioning System)系统, 实施雷达天线方向图校准, 对上海地区金山–芦潮港站雷达基站数据实施校准实验. 结果显示, 天线方向图校准后, 合成流流向和流速的均方根误差分别降低了17.76° 和0.04 m/s, 相关系数分别提高了0.11和0.23. 此外, 分别应用标准差阈值法、箱线图分析法和Isolation Forest算法, 对金山–芦潮港站的合成流场数据进行了质量控制. 3种方法均能有效实现流场边缘和近岸区域的异常值检测, 其中Isolation Forest算法相较于其他方法具备更高的时空敏感度与更广的检测范围. 研究结果表明, 通过改进高频雷达质量控制流程并结合无人机天线方向图校准技术, 可显著改善数据质量, 有效提升海洋动力监测中地波雷达数据的可靠性.

关键词: 高频地波雷达, 天线方向图校准, 数据质量控制, 表层海流

Abstract:

Given their wide coverage, high resolution, and all-weather observational capabilities, high-frequency radars hold considerable potential for ocean current observation and forecasting. In this study, we address two key steps in the radar data processing chain, namely, antenna pattern calibration using an unmanned aerial vehicle (UAV) and anomaly detection using multiple algorithms. A UAV equipped with a beacon–global positioning system was employed for radar antenna pattern calibration. Experiments were conducted at the Jinshan–Luchaogang radar station in Shanghai, China. Following calibration, the root-mean-square errors of current direction and speed decreased by 17.76° and 0.04 m/s, respectively, with corresponding improvements in the correlation coefficients of 0.11 and 0.23. Furthermore, quality control of the radar-derived current data from the Jinshan–Luchaogang area was implemented using three methods: the standard deviation threshold method, boxplot analysis, and Isolation Forest algorithm. All three methods effectively identified anomalies in the marginal and nearshore regions of the observed current fields. Among them, the Isolation Forest algorithm exhibited superior spatiotemporal sensitivity and a broader detection range. These results indicate that combining improvements in the high-frequency radar data quality control with UAV-based antenna calibration can substantially enhance data quality and improve the reliability of high-frequency radar-derived data for ocean dynamic monitoring. Based on these findings, future research is recommended to incorporate multi-source observations and physical constraints to further improve high-frequency radar data quality control and calibration.

Key words: high-frequency radar, antenna pattern calibration, data quality control method, surface current

中图分类号:

TN958.95

吴旭云, 李丕学, 王玉琦. 便携式高频雷达方向图校准及数据质量控制研究[J]. 华东师范大学学报（自然科学版）, 2025, 2025(6): 128-140.

Xuyun WU, Pixue LI, Yuqi WANG. Portable high-frequency radar antenna pattern calibration and multiple data quality control methods[J]. J* E* C* N* U* N* S*, 2025, 2025(6): 128-140.

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参数名	取值	含义及设定依据
树数量	100	100 棵被证明可兼顾效率与稳定性
子样本大小$ \boldsymbol{\psi } $	/	取样本总数与 256 的最小值, 每棵树的最大深度$ h_{\mathrm{m}\mathrm{a}\mathrm{x}}=\lceil\mathrm{l}\mathrm{o}\mathrm{g}_2\left(\mathit{ \boldsymbol{\psi } }\right)\rceil $
异常点比例	/	算法根据训练数据自动推断
特征子集比例	1.0	使用全部特征
随机种子	None	不固定种子