Identification of environmental impacts on GNSS observations based on intrinsic decomposition model

With the increasing Location Based Services (LBS) and Unmanned Aerial Vehicle (UAV) applications of global navigation satellite system (GNSS), identification and diagnosis of environmental impacts on GNSS becomes a vital issue for GNSS services. Among the environment impacts, multipath is an obstinate influence for positioning under complex conditions like the metropolitical regions. Large amount of observations from dense base stations are required for modelling of ionosphere delay. This is especially challenging for localization in low latitude regions like Pear River and Delta areas as GNSS positioning service is frequently disturbed by ionosphere scintillations. Giving this status and problems, this submission presents an intrinsic model method for analysis of environmental influences suffered from both multipath and ionosphere delays in GNSS navigation systems. Theoretical frames include Hilbert Huang transform together with spectrum analysis, in which combinations of GNSS code range and single carrier phase are employed as inputs for decomposition process. Through empirical mode decomposition and spectrum inspections, different intrinsic layers are obtained that representing symbols of observation anomalies derived from both ionosphere scintillation and multipath impacts involved in GNSS observations. The suggested mode decomposition approach needs neither leastsquare adjustment nor minimum number of visible satellites and thus forms an innovative strategy for simultaneous identification for multipath and ionosphere delays involved in GNSS observations.