Comparative Assessment of Scientific and Online GNSS Data Processing Software Based on Indian CORS Subnetwork

The Survey of India has recently established the Indian Continuously Operating Reference Stations (CORS) network to advance geodetic activities and create a precise geodetic infrastructure nationwide. Numerous online and offline software tools are available for high precision Global Navigation Satellite System (GNSS) data processing using precise point positioning (PPP) and relative positioning techniques to facilitate such infrastructure. This article offers an in-depth comparative analysis of various popular offline and web-based software, including Bernese, GNSS at MIT (GAMIT)/Global Kalman filter (GLOBK), GipsyX, AUSPOS, and Online Positioning Users Services (OPUS)-Static, using the newly established Indian CORS subnetwork. The study examines the models employed by these software programs, which are crucial for achieving precise coordinates. The findings show that among offline scientific software, Bernese and GAMIT/GLOBK agree with repeatability in X, Y, and Z at the millimeter level, supporting their use as the superior GNSS data processing software for monitoring stations despite the complex strategies involved in processing the datasets. Although GipsyX provides PPP solutions, it delivers precise results at the subcentimeter level except for a few outliers. AUSPOS, based on Bernese v5.2, with subtle changes, shows good results, but complexities may arise when handling large datasets. OPUS-Static uses a combination of three international GNSS services and/or the National Geodetic Survey CORS as reference stations to compute a solution, resulting in extremely long baselines, which in turn compromises accuracy with repeatability values reaching up to 4 cm in Y coordinates for a few stations. Some statistical tests, such as Bartlett’s test, the Welch analysis of variance test, and the Games–Howell test, were also applied to compare the population mean and variances of X, Y, and Z coordinates. These tests show that the population means of Bernese and GAMIT/GLOBK were statistically similar for more than 80% of stations, while GipsyX failed the Games–Howell test for pairwise comparison of population means for the majority of the stations when compared with the results of two datasets obtained from Bernese and GAMIT/GLOBK software. This rigorous study aids in understanding the strengths and drawbacks of each software, leading to reliable decision-making strategies for various precise GNSS applications.