A combined algorithm for denoising GNSS-RTK positioning solutions with application to displacement monitoring of a super-high-rise building

Abstract Given that global navigation satellite system (GNSS)-based real-time kinematic (GNSS-RTK) monitoring accuracy is easily interfered with by residual errors, a combined algorithm is proposed for signal denoising with application to the GNSS-RTK positioning solutions of a super-high-rise building; namely, the Tianjin Radio and Television Tower in China. The proposed denoising algorithm is a combination of the Butterworth high-pass filter and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), after which the intrinsic mode function components are selected based on the effective coefficient, the correlation coefficient and the power spectral density. After signal filtering, the structural dynamic deformation is 36.0 mm in the horizontal directions and 48.4 mm in the up-direction. Two orders of natural frequencies of the Tianjin Radio and Television Tower are successfully identified (i.e. 0.1583 Hz and 1 Hz). In addition, the relative error of the fundamental frequency is less than 0.44% compared with previous studies. The results reveal the reliability of the combined Butterworth–CEEMDAN algorithms for dealing with GNSS-RTK measurements. Moreover, the improvement in the GNSS-RTK sampling frequency is conducive to extracting more helpful monitoring information. Furthermore, the dynamic deformation data in this paper indicate that the Tianjin Radio and Television Tower is operating normally.