联合加权小波和EEMD的GNSS坐标时间序列降噪分析

GNSS coordinate time series denoising analysis combined with weighted wavelet and EEMD

  • 摘要: 针对GNSS坐标时间序列中有用信号与噪声难以准确分离这一问题,本文提出加权小波Z变换(weighted wavelet Z-transform, WWZ)和集合经验模态分解(ensemble empirical mode decomposition,EEMD)的降噪方法. 通过对西北地区70个陆态网络连续站垂向坐标时间序列的降噪处理,分别采用均方根误差(root mean squared error,RMSE)、信噪比(signal to noise ratio,SNR)、闪烁噪声(flicker noise,FN)振幅及速度不确定度为评价指标,验证了本文方法的降噪效果在一定程度上优于小波降噪和EEMD降噪. 结果显示:WWZ-EEMD相比小波降噪和EEMD降噪,降噪后信号序列RMSE分别降低了0.331 mm、 0.757 mm,SNR分别提高了1.911 dB、3.635 dB;FN振幅及速度不确定度均有明显改善,验证了本文降噪方法的有效性.

     

    Abstract: Aiming at the problem that it is difficult to accurately separate the useful signal and noise in the GNSS coordinate time series, this paper proposes a noise reduction method based on combined weighted wavelet Z-transform (WWZ) and set empirical mode decomposition (EEMD). Through the noise reduction processing of the vertical coordinate time series of 70 continuous stations in the northwest region, the root mean square error (RMSE), signal-to-noise ratio (SNR), flicker noise (FN) amplitude and velocity uncertainty are used as the evaluation indicators respectively, which verifies that the noise reduction effect of the method in this paper is superior to wavelet noise reduction and EEMD noise reduction to a certain extent. The results show that compared with wavelet denoising and EEMD denoising, the RMSE of signal sequence after denoising is reduced by 0.331 mm and 0.757 mm respectively, and the SNR is increased by 1.911 dB and 3.635 dB respectively; The uncertainty of FN amplitude and velocity has been significantly improved, which verifies the effectiveness of the noise reduction method in this paper.

     

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