Article
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Research on High-Dynamic Tracking Algorithms for FH-BOC Signals
Version 1
: Received: 20 August 2024 / Approved: 20 August 2024 / Online: 20 August 2024 (13:52:48 CEST)
How to cite: Li, X.; Zhao, S.; Hou, X.; Wang, L.; Zhang, Y. Research on High-Dynamic Tracking Algorithms for FH-BOC Signals. Preprints 2024, 2024081445. https://doi.org/10.20944/preprints202408.1445.v1 Li, X.; Zhao, S.; Hou, X.; Wang, L.; Zhang, Y. Research on High-Dynamic Tracking Algorithms for FH-BOC Signals. Preprints 2024, 2024081445. https://doi.org/10.20944/preprints202408.1445.v1
Abstract
With the development of Global Navigation Satellite Systems (GNSS), the quality and anti-jamming capability of satellite navigation signals are crucial. Binary Offset Carrier (BOC) modulation faces issues of false locking due to multi-peak ambiguity in its autocorrelation function, limiting its application. This paper examines FH-BOC modulation, which integrates BOC with frequency hopping technology, significantly improving anti-jamming, anti-multipath performance, and spectral efficiency. To meet the high dynamic tracking demands of FH-BOC signals, this study explores three types of carrier tracking loops: the traditional second-order frequency-locked loop assisted a third-order phase-locked loop, a linear Kalman filter-based tracking algorithm, and an adaptive Kalman filter-based tracking algorithm. A composite code tracking loop is also proposed. Simulations show that the adaptive Kalman filter algorithm achieves high-precision carrier tracking in dynamic environments and quickly converges during transitions. The composite code tracking loop, aided by the carrier loop, ensures precise synchronization of pseudocode and frequency-hopping subcarrier phases, demonstrating the superior performance of FH-BOC modulation in dynamic environments.
Keywords
GNSS; FH-BOC; high dynamic tracking; carrier tracking loop; adaptive Kalman filter; composite code loop
Subject
Engineering, Aerospace Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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