Parallel resolution of large GNSS networks using carrier ranges

Abstract Owing to the increasing numbers of navigation satellites, available frequencies, and tracking stations, the computational efficiency of large GNSS networks has become a critical issue, especially when undifferenced (UD) pseudorange and carrier phase observations are used. By converting UD carrier phases into carrier ranges before implementing the integrated processing of a whole network, the UD calculation time can be greatly decreased. However, because a common multicore hardware platform is not fully utilized to optimize the algorithm, the processing of a whole network is still time consuming. In this paper, this problem is overcome by applying the multicore parallel computing technology, namely the Task Parallel Library (TPL). To improve the processing efficiency of large GNSS networks using UD carrier ranges and based on the task parallelism and data parallelism offered through TPL, the wide-lane (WL) and narrow-lane (NL) fractional cycle biases (FCBs), and carrier ranges are computed in parallel, and the integrated processing of a whole network is performed by establishing the normal equation in parallel and adopting parallel computing for Cholesky decomposition. The proposed strategy is validated using GPS, BDS and Galileo observation data recorded from January 6, 2019, to January 26, 2019 by the IGS network with a global distribution of approximately 500 stations. The average positioning accuracies in the east, north and vertical components are 2.54, 2.34 and 4.41 mm, respectively, and the average SDBS ambiguity fixing rate is 93.18%. The average time consumptions for step 1, 2 and 3 are reduced from 151.45, 248.80 and 44.35 min to 32.20, 52.71 and 14.25 min, respectively, with acceleration ratios of 4.70, 4.72 and 3.11 times, respectively, on a six-core platform.