Volume 39, Number 4, August 2021
|Page(s)||761 - 769|
|Published online||23 September 2021|
An ant colony algorithm model for UAV sense and avoid based on ADS-B
School of Computer Science, Sichuan University, Chengdu 610065, China
In the context of airspace fusion, in order to improve the safety performance of UAV and prevent the occurrence of air collision accidents, an ant colony algorithm model for UAV sense and avoid based on ADS-B monitoring technology is proposed. The model mainly consists of two parts: the deterministic conflict detection model makes the full use of ADS-B information to calculate the geometric distance from the horizontal and vertical planes to identify the conflict target, and the conflict resolution model is based on the ant colony algorithm which introduces the comprehensive heuristic function and sorting mechanism to plan the route again for achieving the collision avoidance. The simulation results show that the conflict detection model can effectively identify the possible threat targets, and the conflict resolution model is not only suitable for the typical two aircraft conflict scenarios, but also can provide a better resolution strategy for the complex multiple aircraft conflict scenarios.
Key words: UAV / sense and avoid / ant colony algorithm / ADS-B
关键字 : 无人机 / 感知与规避 / 蚁群算法 / ADS-B
© 2021 Journal of Northwestern Polytechnical University. All rights reserved.
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