基于无人机遥测无线电的优化无线电频率足迹识别
Yuan Tian1,2, Hong Wen1, Jiaxin Zhou2
1College of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China.
Sensors (Basel, Switzerland)
|August 29, 2024
概括
这项研究引入了一种使用其遥测无线电信号识别无人机 (UAV) 的新方法. 这种新的方法在检测和分类无人机方面实现了高精度,提高了空域安全.
科学领域:
- 电气工程 电气工程
- 计算机科学 计算机科学
- 航空航天工程 航空航天工程
背景情况:
- 无人驾驶飞行器 (UAV) 的扩散需要对空域安全进行强有力的检测和识别.
- 遥测无线电对于视觉视线之外 (BVLOS) 的无人机操作至关重要,它提供了一个独特的信号源用于识别.
研究的目的:
- 开发和评估一种新的无人机识别系统,利用遥测无线电的短暂信号.
- 优化信号检测并提高无人机射频 (RF) 指纹识别的准确性.
主要方法:
- 一个优化的EC-α算法用于暂时信号起点检测.
- 一个卷积神经网络 (CNN) 来从原始I/Q数据中提取特征.
- 使用自组织地图 (SOM) 和拟议的集群信号联合识别 (CSJI) 算法进行集群.
主要成果:
- 在室内测试中,拟议的无人机射频识别系统在30dB SNR下实现了92.3%的平均准确性.
- 与支持矢量机 (SVM) 和K-最接近邻居 (KNN) 算法相比,证明了更高的性能.
- 户外实验证实了开发的识别方法的实际可行性.
结论:
- 基于遥测无线电短暂信号的新型无人机识别框架是有效和准确的.
- 优化的EC-α,CNN,SOM和CSJI算法有助于增强射频指纹识别.
- 这种方法为在关键空域中无人机检测和安全提供了一个有希望的解决方案.
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