Title: An Improved DE-KFL for BOC Signal Tracking Assisted by FRFT in a Highly Dynamic Environment
Author(s): Yiran Luo, Lei Zhang, Naser El-Sheimy
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1525 - 1534
Cite this article: Luo, Yiran, Zhang, Lei, El-Sheimy, Naser, "An Improved DE-KFL for BOC Signal Tracking Assisted by FRFT in a Highly Dynamic Environment," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 1525-1534.
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Abstract: This paper presents a Double Estimator Kalman Filter Loop (DE-KFL), which is assisted by Fractional Fourier Transform (FRFT), for tracking high-dynamic BOC signals. New BOC signals, which can perform better in positioning and spectrum compatibility, are frequently used for the modern Global Navigation Satellite System (GNSS) in modern times. BPSK-LIKE and Double Estimator Technique (DET) algorithms are mostly applied to GNSS receivers to cope with the multi-peaks of the Auto-Correlation Function (ACF) of BOC signals. Since the sub-carrier tracking loop of DET has the performance of a narrow pull-in range, it is more likely to be out of lock under dynamic stress. Partially Matched Filter (PMF) is introduced to implement the acquisition process of BOC signals. Fractional Fourier Transform (FRFT) is also included in the acquisition process to estimate the acceleration of the line-of-sight (LOS) signal, and this technique can enhance the sensitivity of the DE-KFL when tracking BOC signals in a highly dynamic environment. Simulations verify that proposed techniques perform significantly better than the original tracking loop. The proposed DE-KFL assisted by the FRFT (A-DE-KFL) algorithm can obviously improve the sensitivity of the tracking loop for BOC signals in a highly dynamic environment.