大机动多旋翼无人机的轨迹预测拦截算法

doi:10.13229/j.cnki.jdxbgxb.20240040

吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (10): 3416-3422.doi: 10.13229/j.cnki.jdxbgxb.20240040

• 通信与控制工程 • 上一篇

大机动多旋翼无人机的轨迹预测拦截算法

孙铭会¹(),边静远²,车嘉兴³,舒振杰⁴

^1.吉林大学计算机科学与技术学院，长春 130012
^2.优联智控（北京）技术有限公司，北京 101318
^3.北京航空航天大学自动化科学与电气工程学院，北京 100191
^4.中国航空工业集团有限公司中国航空综合技术研究所，北京 100073

收稿日期:2024-01-12 出版日期:2025-10-01 发布日期:2026-02-03
作者简介:孙铭会（1983-），男，副教授，博士.研究方向：计算机应用与技术，计算机视觉，智能人机交互.E-mail： smh@jlu.edu.cn
基金资助:
国家重点研发计划项目(2021YFF0601301)

Trajectory prediction and interception algorithm for large maneuvering multi-rotor UAV

Ming-hui SUN¹(),Jing-yuan BIAN²,Jia-xing CHE³,Zhen-jie SHU⁴

^1.College of Computer Science and Technology，Jilin University，Changchun 130012，China
^2.Unilink Intelligent Control（Beijing） Technology Co. ，Ltd. ，Beijing 101318，China
^3.School of Automation Science and Electrical Engineering，Beihang University，Beijing 100191，China
^4.China Aero?Polytechnology Establishment of AVIC，Beijing 100073，China

Received:2024-01-12 Online:2025-10-01 Published:2026-02-03

摘要/Abstract

摘要：

针对未经许可的拒止无人机在限飞区域内的安全风险以及其难以被反制的问题，提出了利用一架无人机对无证无报备无人机进行高速拦截的算法。本文算法使用导航、控制架构来解决这个问题。导航方面，通过相机与激光雷达的结合，实现了低成本的全向感知，并通过对高精度低频率的激光雷达数据与高频率低精度的视觉数据进行融合，得到精确的目标位置估计与追踪。控制方面，采用基于轨迹预测的动态权限分配控制方法，以实现对大机动无人机的有效反制。最终，通过实验及仿真验证了本文算法的有效性，结果表明：对不小于12 m/s的拒止无人机的锁定成功率大于90%，拦截成功率高于85%。

关键词: 智能控制与机器人, 轨迹预测, 融合感知, 位置估计

Abstract:

Aiming at the security risk of the unauthorized rejected UAV in the restricted flying area， and the problem that it is difficult to counter， this paper proposes an algorithm to use a UAV to intercept the unlicensed and uninformed UAV at high speed. Our algorithm uses a navigation and control architecture to solve this problem. In the aspect of navigation， low-cost omnidirectional perception was realized through the combination of camera and laser radar. Through the fusion of high precision and low frequency lidar data and high frequency and low precision vision data， accurate target position estimation and tracking are obtained. In the control aspect， the dynamic authority allocation control method based on trajectory prediction is used to realize the effective countermeasures against the large maneuvering UAV. Finally， the effectiveness of the proposed algorithm is verified by experiments and simulations. It is verified that the proposed algorithm can lock the denied UAV with a success rate of more than 90% and intercept the UAV with a success rate of more than 85%.

Key words: intelligent control and robotics, trajectory prediction, fusion perception, position estimation

中图分类号:

TP391.8

孙铭会,边静远,车嘉兴,舒振杰. 大机动多旋翼无人机的轨迹预测拦截算法[J]. 吉林大学学报(工学版), 2025, 55(10): 3416-3422.

Ming-hui SUN,Jing-yuan BIAN,Jia-xing CHE,Zhen-jie SHU. Trajectory prediction and interception algorithm for large maneuvering multi-rotor UAV[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(10): 3416-3422.

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参考文献 13

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[6]	Wang M, Yang W Z, Wang L J, et al. FE-YOLOv5: feature enhancement network based on YOLOv5 for small object detection[J]. Journal of Visual Communication and Image Representation, 2023(90): No.103752.
[7]	Yang Z T, Sun Y N, Liu S, et al. 3DSSD: point-based 3D single stage object detector[C]∥IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), Seattle, USA, 2020:No. 01105.
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Sensor	Update rate	Measurements
Camera	30 Hz	Position
Lidar	10 Hz	Position

大机动多旋翼无人机的轨迹预测拦截算法

Trajectory prediction and interception algorithm for large maneuvering multi-rotor UAV

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项目	一次拦截成功率/%	多次拦截成功率/%
仿真	100	100
实飞	>85	100