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

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Abstract

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.

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Authors and Affiliations

  1. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    ChenXi Lu, YunHua Tan, BoCheng Zhu & LeZhu Zhou

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  1. ChenXi Lu
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  2. YunHua Tan
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  3. BoCheng Zhu
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  4. LeZhu Zhou
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Correspondence to YunHua Tan.

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Lu, C., Tan, Y., Zhu, B. et al. Improved innovation-based adaptive Kalman filter for dual-frequency navigation using carrier phase. Sci. China Inf. Sci. 53, 2653–2663 (2010). https://doi.org/10.1007/s11432-010-4117-3

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  • DOI: https://doi.org/10.1007/s11432-010-4117-3

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