Abstract
Since the traditional current statistical Kalman (CS-Kalman) filter doesn’t perform well enough when used in high-dynamic carrier tracking, an carrier tracking algorithm of Kalman filter based on combined maneuvering target model composed of high dynamic CS-Kalman filter and steady-state self-adaptive CS-Kalman filter is presented. The proposed algorithm achieves stable and accurate carrier synchronization by adjusting the CS-Kalman filter type and parameter corresponding to the dynamic condition in real time. Simulation results show that compared with the traditional CS-Kalman algorithm, the proposed algorithm is more realistic, practical valuable and adaptable in high dynamic environment.
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Xiong, Z., Ren, S., Liu, C., An, J. (2016). A Carrier Tracking Algorithm of Kalman Filter Based on Combined Maneuvering Target Model. In: Jia, Y., Du, J., Li, H., Zhang, W. (eds) Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48386-2_29
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DOI: https://doi.org/10.1007/978-3-662-48386-2_29
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