Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/92771
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Title: Performance assessment of GNSS scalar and vector frequency tracking loops
Authors: Dou, J
Xu, B 
Dou, L
Issue Date: Feb-2020
Source: Optik, Feb. 2020, v. 202, 163552
Abstract: This paper focuses on two types of frequency lock loops (FLL) in Global Navigation Satellite System (GNSS) receivers, namely the conventional scalar frequency lock loop (SFLL) and the vector frequency lock loop (VFLL).The VFLL has been proven to have a better tracking performance than the SFLL in scenarios such as intermittent signal outages, high dynamics, etc. However, the FLL tracking performance under the equivalent noise bandwidth has not been explored in literature. To do this, we implemented three kinds of FLL, i.e., the SFLL, the weighted least square-based vector frequency loop (WLS-VFLL), and the extended Kalman filter-based vector tracking loop (EKF-VFLL). All these FLLs have the same noise bandwidth, based on which we made a fair comparison between them. The experimental static data and simulated high- dynamic data have been tested. Results show that the EKF-VFLL has a similar tracking performance with WLS-VFLL under static environment, both better than the SFLL. In high- dynamic environment, the advantages of EKF-VFLL are more prominent than the other two methods. Furthermore, EKF-VFLL takes the longest time in terms of computational efficiency.
Keywords: Equivalent noise bandwidth
Extended Kalman filter (EKF)
Frequency lock loop (FLL)
Global navigation satellite system (GNSS)
Weighted least square (WLS)
Publisher: Urban & Fischer
Journal: Optik 
ISSN: 0030-4026
EISSN: 1618-1336
DOI: 10.1016/j.ijleo.2019.163552
Rights: © 2019 Elsevier GmbH. All rights reserved.
©2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Dou, J., Xu, B., & Dou, L. (2020). Performance assessment of GNSS scalar and vector frequency tracking loops. Optik, 202, 163552 is available at https://doi.org/10.1016/j.ijleo.2019.163552.
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