Kinematic Zenith Tropospheric Delay Estimation with GNSS PPP in Mountainous Areas

Abstract

The use of global navigation satellite systems (GNSS) precise point positioning (PPP) to estimate zenith tropospheric delay (ZTD) profiles in kinematic vehicular mode in mountainous areas is investigated. Car-mounted multi-constellation GNSS receivers are employed. The Natural Resources Canada Canadian Spatial Reference System PPP (CSRS-PPP) online service that currently processes dual-frequency global positioning system (GPS) and Global’naya Navigatsionnaya Sputnikovaya Sistema (GLONASS) measurements and is now capable of GPS integer ambiguity resolution is used. An offline version that can process the above and Galileo measurements simultaneously, including Galileo integer ambiguity resolution is also tested to evaluate the advantage of three constellations. A multi-day static data set observed under open sky is first tested to determine performance under ideal conditions. Two long road profile tests conducted in kinematic mode are then analyzed to assess the capability of the approach. The challenges of ZTD kinematic profiling are numerous, namely shorter data sets, signal shading due to topography and forests of conifers along roads, and frequent losses of phase lock requiring numerous but not always successful integer ambiguity re-initialization. ZTD profiles are therefore often only available with float ambiguities, reducing system observability. Occasional total interruption of measurement availability results in profile discontinuities. CSRS-PPP outputs separately the zenith hydrostatic or dry delay (ZHD) and water vapour content or zenith wet delay (ZWD). The two delays are analyzed separately, with emphasis on the more unpredictable and highly variable ZWD, especially in mountainous areas. The estimated delays are compared with the Vienna Mapping Function 1 (VMF1), which proves to be highly effective to model the large-scale profile variations in the Canadian Rockies, the main contribution of GNSS PPP being the estimation of higher frequency ZWD components. Of the many conclusions drawn from the field experiments, it is estimated that kinematic profiles are generally determined with accuracy of 10 to 20 mm, depending on the signal harshness of the environment.

Response of Meiyu process considering the temporal and spatial characteristics of GNSS PWV

“…ZTD is primarily composed of two components: ionospheric delay and tropospheric delay. The ionospheric delay can be eliminated by dualfrequency receivers, which remove approximately 99% of its effects [11]. The tropospheric delay consists of Zenith Hydrostatic Delay (ZHD) and Zenith Wet Delay (ZWD).…”

Instantaneous Sub-meter Level Precise Point Positioning of Low-Cost Smartphones

“…Undifferenced and uncombined PPP technology is a high-precision data processing method that can make full use of the raw GNSS observations and accurately retrieve ionospheric slant TEC (STEC) and zenith tropospheric delay (ZTD) data. Therefore, PPP-derived STEC (Liu et al, 2018; and PPP-derived ZTD (Gratton et al, 2021;Zhao et al, 2018) are proposed as effective reference values to evaluate the accuracy of ionospheric and tropospheric models.…”

Sensitivity of Shipborne GNSS Estimates to Processing Modeling Based on Simulated Dataset

“…The main component of ZTD is the Zenith Hydrostatic Delay (ZHD), which depends only on the atmospheric pressure at the height of the antenna [ 10 , 11 ]. The ZHD component can be estimated from empirical models or meteorological surface measurements and set up as an a priori component in the modeling part before calculating the other PPP variables [ 12 , 13 , 14 ]. Indeed, the a priori value of ZHD can be correctly computed thanks to a simple pressure, temperature, and humidity sensor located near the GNSS antenna, or by using a reanalysis such as ERA5 or a model such as VMF3 [ 11 , 15 ].…”