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Quality Control of Compact High-Frequency Radar-Retrieved Wave Data
IEEE Transactions on Geoscience and Remote Sensing ( IF 8.2 ) Pub Date : 2021-02-01 , DOI: 10.1109/tgrs.2020.2997356
Zhen Tian , Yingwei Tian , Biyang Wen

Based on the sea surface scattering mechanism of radio wave, compact high-frequency surface wave radar that employs the direction finding technology also shows promising potential for remotely mapping of ocean wave parameters. However, due to the low signal-to-noise ratio (SNR) of scattered echoes, the diverse external interference and clutter signals, other unresolved measurement uncertainties, the quality (such as accuracy, temporal, and spatial coverage rates) of wave maps are often limited. In this article, a novel, real-time, data quality control method is proposed to alleviate these issues. A comprehensive three-stage processing scheme is established, including the range-Doppler spectral processing, the spatial-grid processing, and the temporal-scale Kalman filtering. The first two stages aim to improve the echo signal quality and reduce the spatial gaps, respectively. The third stage is designed to mitigate the estimation error using an autoregression prediction model and to relate the observation error variance to the SNR of second-order Doppler spectral peak. A detailed verification and performance analysis between the field radar data and in situ ground truth data over one-month period is carried out, indicating that the proposed method can improve the reliability of wave maps with respect to the conventional Doppler spectral smoothing or averaging method, particularly in low sea state (i.e., low SNR) scenarios.

中文翻译:

紧凑型高频雷达波数据的质量控制

基于无线电波的海面散射机制,采用测向技术的紧凑型高频面波雷达在远距离测绘海浪参数方面也具有广阔的前景。然而,由于散射回波的信噪比 (SNR) 低、外部干扰和杂波信号的多样性以及其他未解决的测量不确定性,波图的质量(如精度、时间和空间覆盖率)受到影响。往往有限。在本文中,提出了一种新颖的实时数据质量控制方法来缓解这些问题。建立了全面的三级处理方案,包括距离多普勒频谱处理、空间网格处理和时间尺度卡尔曼滤波。前两个阶段分别旨在提高回波信号质量和减少空间间隙。第三阶段旨在使用自回归预测模型减轻估计误差,并将观测误差方差与二阶多普勒频谱峰值的 SNR 相关联。对现场雷达数据和现场地面实况数据进行了一个月的详细验证和性能分析,表明该方法相对于传统的多普勒频谱平滑或平均方法可以提高波图的可靠性,特别是在低海况(即低 SNR)情况下。第三阶段旨在使用自回归预测模型减轻估计误差,并将观测误差方差与二阶多普勒频谱峰值的 SNR 相关联。对现场雷达数据和现场地面实况数据进行了一个月的详细验证和性能分析,表明该方法相对于传统的多普勒频谱平滑或平均方法可以提高波图的可靠性,特别是在低海况(即低 SNR)情况下。第三阶段旨在使用自回归预测模型减轻估计误差,并将观测误差方差与二阶多普勒频谱峰值的 SNR 相关联。对现场雷达数据和现场地面实况数据进行了一个月的详细验证和性能分析,表明该方法相对于传统的多普勒频谱平滑或平均方法可以提高波图的可靠性,特别是在低海况(即低 SNR)情况下。
更新日期:2021-02-01
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