Improved innovation-based adaptive Kalman filter for dual-frequency navigation using carrier phase  

作　　者：LU ChenXi,TAN YunHua ,ZHU BoCheng & ZHOU LeZhu School of Electronics Engineering and Computer Science,Peking University,Beijing 100871,China 

出　　处：《Science China(Information Sciences)》2010年第12期2653-2663,共11页中国科学（信息科学）（英文版）

摘　　要：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 demonstrate the validity and efficiency of the algorithm.

关 键 词：NAVIGATION adaptive Kalman filter carrier phase 

分 类 号：TN967[电子电信—信号与信息处理]