GNSS Data Fusion with Functional and Stochastic ModelConstraints as well as Property Analysis

Objective The data fusion for GNSS processing often have some functional model constraints amongparameters or some stochastic model(prior information for total or part parameters)constraints.Inthis paper,the parameter estimators for dual functional and stochastic information constraints arepresented in least squares principle,and the posteriori precision estimators are also derived.As somespecial examples,the parameter estimators with only functional model constraints or stochastic modelconstraints are derived respectively.The properties of the data fusion with dual constraints are dis-cussed in theory.By analyzing the influences of the functional constraints,it is pointed that any errorin the functional model constraints will result in compulsive twist in estimated parameters which iscalled“hard twist”.The errors of the stochastic model constraints will also result in bias of parameterestimates,which is called“soft bias”.An actual GPS network with measurements of two epochs,2011and 2012,are employed in the data fusion,by which the contribution and effects of the function-al and stochastic model constraints are analyzed.