###### Abstract
Most of the observation errors will be compensated by conventional models, while the corresponding residuals will be modeled as parameters. Thus, PPP can also reach high accuracy (i.e., centimeter or even millimeter level) after ambiguity convergence. Therefore, PPP has potential capability in displacement monitoring. For example, [PERSON] et al. [4] demonstrated the performance of the real-time ambiguity-fixed PPP using the 5 Hz Global Positioning System (GPS) data during the El Mayor-Cucapah earthquake (Mw7.2). Results illustrated that the PPP-based displacements are in accordance with the accelerometer-based ones at centimeter level. According to works in [PERSON] et al. [17], two-thousand 24 h displacements at ninety-nine stations in Europe were analyzed by introducing GLONASS data into high-rate GPS PPP. Results reflected that the integration of GPS and GLONASS can further reduce the noise of high-rate PPP. Meanwhile, it also illustrates that the high-rate multi-GNSS PPP could be further amplified by using sidereal filtering. [PERSON] et al. [3] studied the key sections of the integration between GNSS and strong motion records, which could be a guide for earthquake real-time monitoring and early warning. Theoretically, there would be atmospheric disturbances before or after seismic activity [18; 19; 20]. However, researchers such as [PERSON] [21] and [PERSON] et al. [22] maintained that the atmospheric earthquake precursor is controversial and cannot be used to predict earthquakes [23]. Nevertheless, there are still many research works focusing on the inter-relationship between earthquake preparation and atmospheric disturbances (i.e., ionospheric disturbance). For example, a study by [PERSON] et al. [24] showed an anomalous disturbance of ionosphere electron density before the Alaska earthquake in 1964. [PERSON] et al. [25] used GIM (Global Ionosphere Map) data to present the variations of Total Electron Content (TEC) during 35 earthquakes (Mw \(\geq\) 6.0) that occurred from 1 May 1998 to 30 April 2008 in China. This method was also employed to analyze the seismo-ionospheric anomalies during the Wenchuan earthquake (Mw 7.9), China, on 12 May 2008. [PERSON] et al. [26] analyzed the ionospheric anomalous phenomenon of strong earthquakes (Mw5.0) that occurred principally in and around the seismically active regions from 2006 to 2009 in Uzbekistan. The results showed that the ionospheric TEC may increase or decrease abnormally before or during earthquakes. [PERSON] et al. [27] found that two affairs of coseismic ionospheric disturbances were observed after the Wenchuan earthquake at 06:28 UT on 12 May 2008 through a GPS network in China. According to their conclusions, such two coseismic ionospheric disturbances were induced by the acoustic gravity waves that were active due to the partial transformation of the acoustic waves (because of the earthquake energy release). [PERSON] et al. [28] found that the seismic ionospheric anomalous phenomenon may occur within 10 days of an earthquake rupture by applying a temporal and spatial statistical analysis on the GPS- and GIM-TEC data from the three earthquakes (\(\geq\)Mw7.0) near the Nepal-Iran-Iraq border in the course of 2015-2017. The reason for such positive anomalies in TEC might be owing to the existence of enormous energy in the epicenter before the earthquake ruptures. [PERSON] et al. [1] combined the ground displacement and ionospheric TEC in the Total Variometric Approach (TVA). This method was utilized in 2015 Illapel earthquake (Mw 8.3). The results showed that the ground motion and the TEC perturbation were detected at 30 s and 9.5 min after the rupture, respectively. The GNSS data stream by TVA opens new orientations to real-time warning systems for tsunami genesis estimation. In general, those research works at present are chiefly based on dual-frequency GPS data which is a high cost. Thus, this paper aims to provide a method that can present the displacement and ionospheric disturbance simultaneously and economically.