Issue |
JNWPU
Volume 39, Number 4, August 2021
|
|
---|---|---|
Page(s) | 761 - 769 | |
DOI | https://doi.org/10.1051/jnwpu/20213940761 | |
Published online | 23 September 2021 |
An ant colony algorithm model for UAV sense and avoid based on ADS-B
基于ADS-B的无人机感知与规避蚁群算法模型
School of Computer Science, Sichuan University, Chengdu 610065, China
Received:
27
November
2020
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.
摘要
在空域融合背景下,为了提高无人机安全性能、防止空中碰撞事故的发生,提出一种基于ADS-B监视技术的无人机感知与规避蚁群算法模型。该模型主要由两部分组成:确定型冲突探测模型和冲突解脱模型。前者充分利用ADS-B信息从水平和垂直面进行几何距离判定来确定冲突目标,后者则基于引入了综合启发函数和排序机制的蚁群算法进行航路重规划来实现避撞。经仿真实验验证,该探测模型能有效识别可能威胁目标,而解脱模型不仅适用于典型的双机冲突场景,也能为复杂的多机冲突场景提供较优质的解脱策略。
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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