Rapid Search and Detection Technology for Non-Cooperative Unmanned Aerial Vehicle Ground Stations and Operators

JIN Xiaolong; HOU Bo; FAN Zhiliang; YIN Zhongjie

doi:10.7652/xjtuxb202507004

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Rapid Search and Detection Technology for Non-Cooperative Unmanned Aerial Vehicle Ground Stations and Operators

Special Topic　Academic Papers of the 27th Annual Meeting of the China Association for Science and Technology | 更新时间：2025-07-09

- Rapid Search and Detection Technology for Non-Cooperative Unmanned Aerial Vehicle Ground Stations and Operators
- Journal of Xi’an Jiaotong University Vol. 59, Issue 7, Pages: 36-45(2025)
- 作者机构：
  
  火箭军工程大学作战保障学院， 710025，西安
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202507004
  CLC： TP391.4
- Received：03 December 2024，
  
  Online First：09 April 2025，
  
  Published：10 July 2025
- 稿件说明：
移动端阅览
JIN Xiaolong, HOU Bo, FAN Zhiliang, et al. Rapid Search and Detection Technology for Non-Cooperative Unmanned Aerial Vehicle Ground Stations and Operators[J]. Journal of Xi’an Jiaotong University, 2025, 59(7): 36-45.
DOI：

JIN Xiaolong, HOU Bo, FAN Zhiliang, et al. Rapid Search and Detection Technology for Non-Cooperative Unmanned Aerial Vehicle Ground Stations and Operators[J]. Journal of Xi’an Jiaotong University, 2025, 59(7): 36-45. DOI： 10.7652/xjtuxb202507004.

摘要

针对现有无人机反制技术仅对无人机本体进行干扰拦截，导致“治标而不治本”的问题，提出了一种非合作无人机地面站及飞手快速搜寻检测技术。首先，利用时间调制阵列天线信号测向方法测定非合作无人机地面站方位；然后，基于该方位信息使用透视投影计算地面站操作飞手在无人机挂载视觉设备中的投影尺寸；最后，重构轻量化目标检测网络，并通过目标投影尺寸信息辅助的网络选择机制实现飞手的快速检测。仿真和实验结果表明：所提技术可实现地面站及飞手的快速搜寻检测，其中在无人机平台上单次测向平均用时9.67 ms，平均测向误差1.08°；对飞手目标的图像检测帧率平均提升了52.98%，重构目标检测网络参数量平均减少59.6%，浮点运算速度平均下降37.7%。所提技术可为非合作无人机反制提供全新思路和方法。

Abstract

To address the limitations of existing anti unmanned aerial vehicle (anti-UAV) technologies

which only focus on interfering with and intercepting UAVs themselves

resulting in a “symptomatic rather than fundamental” solution

a rapid search and detection technology aimed at non-cooperative UAV ground stations and operators is proposed. First

the direction of the non-cooperative UAV ground station is determined using a time-modulated array antenna signal direction-finding method. Then

based on this directional information

perspective projection is employed to calculate the projected size of the ground station operator in the UAV-mounted visual device. Finally

a lightweight target detection network is reconstructed

and a network selection mechanism assisted by target projection size information is implemented to achieve rapid operator detection. Simulation and experimental results demonstrate that the proposed technology enables fast search and detection of ground stations and operators. Specifically

the average single direction-finding time on the UAV platform is 9.67 ms

with an average direction-finding error of 1.08°. The image detection frame rate for operator targets is improved by an average of 52.98%

while the reconstructed target detection network reduces the parameter count by 59.6% and floating-point operations per second by 37.7% on average. The proposed technology provides a novel approach and methodology for anti-UAV measures.

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references

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