E3S Web Conf.
Volume 94, 2019International Symposium on Global Navigation Satellite System 2018 (ISGNSS 2018)
|Number of page(s)||5|
|Section||GNSS Today and Future|
|Published online||08 May 2019|
Autonomous Base Station Placement for Localization of the GNSS Interference Source
Mechanical and Aerospace Engineering and Automation and System Research Institute, Seoul National University, Gawnak-Gu, Seoul 08826, Republic of Korea
2 BK21+ Transformative Training Program for Creative Mechanical and Aerospace Engineers, Seoul National University, Gawnak-Gu, Seoul 08826, Republic of Korea
3 Mechanical and Aerospace Engineering and the Institute of Advanced Aerospace Technology, Seoul National University, Gawnak-Gu, Seoul 08826, Republic of Korea
* Corresponding author: email@example.com
This paper presents the control strategy of autonomous base station placement for localization of the GNSS interference source. The proposed algorithm deals with the optimization of the base station trajectory for target motion analysis based on bearing only tracking problem. The control strategy of the proposed algorithm is designed to maximize a cost function which is generally a functional of the Fisher information matrix. Compared to the optimal control methods, the proposed algorithm is easy to be designed and implemented, and constraints of multiple base stations’ trajectories can be effectively included. In addition, the proposed algorithm also considered target’s dynamics that is both uncertain and random, and there are multiple base stations for observing the target. In order to verify the performance of the proposed algorithm, simulation was performed with dynamic target case in the 2D scenario. It is assumed that the base stations’ networks have non-fully connected topology. According to the simulation results, it was confirmed that the proposed algorithm presents a flexible control strategy of autonomous multiple base stations’ placement for bearing only target tracking system.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.