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A new adaptive Kalman filtering algorithm for dual-frequency navigation using carrier phase is presented.This algorithm gives consideration to both robustness and sensitivity by combining the two main approaches of adaptive Kalman filtering based on innovation-based adaptive estimation(IAE) and fading filtering.Applicable to the navigation using carrier phase measurements typically,this algorithm can balance the weights of observations and predicted states preferably.Applications to both practical static data and kinetic simulations are presented to demonstrate the validity and efficiency of the algorithm.
A new adaptive Kalman filtering algorithm for dual-frequency navigation using carrier phase is presented. This algorithm gives consideration to both robustness and sensitivity by combining the two main approaches of adaptive Kalman filtering based on innovation-based adaptive estimation (IAE) and fading filtering. Applicable to the navigation using carrier phase measurements typically, this algorithm can balance the weights of observations and predicted states preferably. Applications to both practical static data and kinetic simulations are presented to the validity and efficiency of the algorithm.