Abstract: | Abstract—In hostile environments, GNSS is a potentially unreliable solution for self-localization and navigation. Many systems only use an IMU as a backup system, resulting in integration errors which can dramatically increase during mission execution. We suggest using a fighter radar to illuminate satellites with known trajectories to enhance the self-localization information. This technique is time-consuming and resource-demanding but necessary as other tasks depend on the self-localization accuracy. Therefore, an adaption of classical resource management frameworks is required. We propose a quality of service based resource manager with capabilities to account for inter-task dependencies to optimize the self-localization update strategy. Our results show that this leads to adaptive navigation update strategies, mastering the trade-off between self-localization and the requirements of other tasks. Index Terms—Q-RAM, Quality of Service, Radar, Navigation, Resource Management, Positioning, Cognitive Radar, GNSS |
Published in: |
2023 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 24 - 27, 2023 Hyatt Regency Hotel Monterey, CA |
Pages: | 59 - 66 |
Cite this article: | Müller, Tobias, Durst, Sebastian, Marquardt, Pascal, Brüggenwirth, Stefan, "Quality of Service Based Radar Resource Management for Navigation and Positioning," 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2023, pp. 59-66. https://doi.org/10.1109/PLANS53410.2023.10140094 |
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