<p>Although global navigation satellite system-precise point positioning (GNSS-PPP) is contemplated for monitoring the dynamic deformation of large-scale engineering structures, its monitoring accuracy is relatively low due to background noise interference. Therefore, this paper aims to investigate the feasibility of GNSS-PPP for dynamic deformation monitoring through a case study. Aiming at the disturbance of background noise, a novel algorithm that integrates the correlation coefficient-based Butterworth filter and the complete ensemble empirical mode decomposition with adaptive noise (Butterworth-CC-CEEMDAN) is proposed to improve the monitoring performance of GNSS-PPP. The simulation experiment results indicate that the proposed correlation coefficient-based Butterworth method could address the temporal lag effect of the traditional Butterworth low-pass filter. Specifically, the Butterworth-CC filtered signal enhances the signal-to-noise ratio by 317% and correlation coefficient by 60.5%, while it concurrently reduces the standard deviation by 38.2% compared to the original noisy signal. On this basis, the Butterworth-CC-CEEMDAN signal exhibits a 6.22% increase in SNR compared to the correlation coefficient-based Butterworth-filtered signal. A field experiment is further performed using GNSS-PPP combined with the Butterworth-CC-CEEMDAN for monitoring a super high-rise structure, namely Tianjin Tower. The field experiment results reveal that the relative dynamic displacements of Tianjin Tower range within ± 150 mm. Besides, a fundamental frequency of 0.1586 Hz is identified from the monitored signal, which is aligning closely with finite element analysis results and previous measurements and thereby affirming its safe operation. As GNSS-PPP exhibits its capability to dynamic deformation monitoring of super high-rise structures, it can be considered for integration into long-term structural health monitoring system.</p>