Abstract
In complex environments, signals are inevitably subject to phenomena such as reflection, refraction, diffraction, and obstruction, which result in significant unmodeled errors like colored noise, residual systematic errors, and other special outliers. Consequently, the achievement of high-precise and high-reliable global navigation satellite systems (GNSS) precise point positioning (PPP) is not a readily solvable problem in complex environments, especially in varying terrain topography. This paper proposed the resilient inequality constrained GNSS kinematic PPP method considering the terrain topography to improve the abnormal positioning results caused by unmodeled errors. Specifically, the proposed method is composed of the adaptive inequality constraint with dynamic penalty function and the timing-varying inequality considering the terrain topography. Two representative experiments including one set of designed data and three sets of daily measured data were conducted. The results show that the proposed method can improve the positioning results resulting from the unmodeled errors while preserving the trend of the original data. Typically, the proposed method decreases the standard deviations by 2.47, 0.25, and 1.46 cm in the U direction of the three real datasets, respectively. Consequently, the proposed method exhibits prospects in precision and reliability for complex environments.
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