Abstract
Joint use of observations from multiple global navigation satellite systems (GNSS) is advantageous in high-accuracy positioning. However, systematic errors in the observations can significantly impact on the positioning accuracy if such errors cannot be properly mitigated. The errors can distort least squares estimations and also affect the results of variance component estimation that is frequently used to determine the stochastic model when observations from multiple GNSS are used. We present an approach that is based on the concept of semiparametric estimation for mitigating the effects of the systematic errors. Experimental results based on both simulated and real GNSS datasets show that the approach is effective, especially when applied before carrying out variance component estimation.
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