Abstract
Systematic errors, such as multipath and residual atmospheric errors in GPS double difference carrier phase observations, are the main error sources for high precision GPS applications. The complicated properties of systematic errors limit the modelling and mitigation of these errors when parametric models are used. In this paper, a new approach based on wavelet analysis is developed to tackle them. Wavelet transform is used as a tool to separate systematic errors from the signal. The signal here is double differential phase observation, which is an input for wavelet transform system. Through multi-step decomposition for original double differential observation, systematic errors identity is exhibited at a certain scale in the decomposition and the double differential observation is then reconstructed by a filtering to the signal with systematic errors eliminated. The newly formed observation is then used as the input for baseline adjustment unit to achieve desired positioning efficiency. Experiment and analysis is conducted to show the applicability of the proposed approach.
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