Abstract: | Dual-Frequency, Dual-Constellation Local-Area DGNSS (DFDC LADGNSS) modernizes and expands upon L1-based LADGPS to support autonomous vehicles with improved system availability and robustness against ionospheric disturbances. Recent research has evaluated several different LADGNSS smoothing strategies using measurements on GPS L1/L5 and Galileo E1/E5a frequencies to determine the optimal approach under nominal conditions. However, under anomalous ionospheric conditions, the optimal smoothing procedure may be different from the one preferred under nominal conditions. In addition, and system performance greatly depends on the ionospheric monitoring algorithm when a Single Frequency (SF) or Divergence-Free (DF) smoothing process is used. To examine this problem, the performance of SF and DF smoothing processes is evaluated by simulation in terms of Maximum Ionosphere-Induced Vertical Errors (MIEVs), which quantify the anomalous ionospheric impact on DFDC LADGNSS. IonosphereFree (IF) smoothing, which removes almost all ionospheric delay impacts, is evaluated based on its nominal (H0) Vertical Protection Level (VPL). A dual frequency ionospheric gradient monitor is also introduced to fully take advantage of multiple-frequency measurements. MIEVs and VPLs are generated for 27-satellite GPS and Galileo constellations to determine which smoothing and monitor strategies give the best performance (lowest MIEVs or VPLs) under anomalous ionospheric conditions. |
Published in: |
Proceedings of the 2022 International Technical Meeting of The Institute of Navigation January 25 - 27, 2022 Hyatt Regency Long Beach Long Beach, California |
Pages: | 1156 - 1174 |
Cite this article: |
Nam, Gihun, Min, Dongchan, Kim, Noah Minchan, Lee, Jiyun, Pullen, Sam, "Optimal Smoothing and Monitor Strategies for Dual-Frequency Dual-Constellation (DFDC) LADGNSS under Anomalous Ionospheric Conditions," Proceedings of the 2022 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2022, pp. 1156-1174.
https://doi.org/10.33012/2022.18166 |
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