高噪声状态下潮汐信号提取

Tidal signal extraction under high noise conditions

  • 摘要: GNSS浮标由于特殊的观测环境,数据质量普遍较差,这导致其坐标时间序列存在较高的噪声,并且存在某些阶跃(或称跳变). 针对该问题,本文提出了一种基于滑动窗的双边累积和(cumulative sum,CUSUM)的阶跃探测和修复方法,该方法在非侵入式负荷监测领域已有广泛应用. 对于GNSS精密单点定位(precise point positioning, PPP)计算所得海面高程(sea surface height, SSH),用该算法探测阶跃并修复后与验潮站参考数据对比,其均方根误差(root mean square error, RMSE)提升了75.5%,相关性提升了7.46%;对于从修复前后的高程时间序列提取的有效波高(significant wave height, SWH),以海洋浮标(wavebuoy,WB)测量结果作为参考,其RMSE提升了65.22%,相关性提升了208.28%. 研究结果表明:该方法可以有效提高GNSS技术反演海浪参数的精确度和可靠性,为GNSS技术在潮汐信号提取提供有价值的参考,对于提高海洋工程安全性和经济效益具有积极意义.

     

    Abstract: In response to the accuracy issue in tidal signal calculation during Global Navigation Satellite System (GNSS) buoy ocean measurements, particularly in high-noise conditions affecting wave parameter calculations, this paper proposes a novel step detection and restoration method based on the sliding window cumulative sum (CUSUM) algorithm, which has been extensively utilized in non-intrusive load monitoring. The algorithm is applied to detect and correct step discontinuities in the sea surface height (SSH) obtained from precise point positioning (PPP) computations and the significant wave height (SWH) extracted from the SSH time series. The performance of the method is evaluated by comparing it with reference data from tide gauge stations and dedicated wave buoys. The results demonstrate that the proposed method significantly improves the accuracy and reliability of GNSS technology in inverting wave parameters. The root mean square error (RMSE) of SSH is enhanced by 75.5%, and the correlation is increased by 7.46%. Moreover, the RMSE of SWH is improved by 65.22%, and the correlation is boosted by 208.28%. These findings underscore the effectiveness of the proposed method in enhancing the accuracy of wave parameter extraction using GNSS technology. The method's implications for enhancing marine engineering safety and economic benefits are also highlighted, making it a valuable contribution to GNSS step detection and providing valuable insights into the extraction and application of tidal signals using GNSS technology.

     

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