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无人机检测和分类技术的进步和挑战:一篇最先进的技术审查
Ulzhalgas Seidaliyeva1, Lyazzat Ilipbayeva2, Kyrmyzy Taissariyeva1
1Department of Electronics, Telecommunications and Space Technologies, Satbayev University, Almaty 050013, Kazakhstan.
Sensors (Basel, Switzerland)
|January 11, 2024
概括
本综述详细介绍了检测和分类无人机 (UAV) 或无人机方面的进展. 它强调了挑战,并探索了各种检测方法,以应对无人机活动带来的安全风险日益增加.
科学领域:
- 航空航天工程 航空航天工程
- 计算机科学 计算机科学
- 电气工程 电气工程
背景情况:
- 无人驾驶飞行器 (UAV) 或无人机在民用和军事领域提供了好处,但也带来了空域入侵和隐私侵犯等风险.
- 无人机日益普及,需要先进的检测和分类系统来缓解安全问题.
研究的目的:
- 提供当前无人机检测和分类技术的全面审查.
- 突出解决无人机动态行为,尺寸和速度所带来的挑战的新策略.
- 检查各种检测方式的优点和局限性.
主要方法:
- 关键检测方式的分类:雷达,射频 (RF),声学和基于视觉的方法.
- 调查与无人机特征相关的威胁和挑战.
- 讨论传感器融合和Wi-Fi,蜂和物联网网络等替代检测方法.
主要成果:
- 确定每个初级检测模式的独特优势和局限性.
- 强调传感器融合对于提高检测准确性和效率的关键作用.
- 探索新兴的检测策略,以应对不断变化的无人机威胁.
结论:
- 先进的检测和分类系统对于管理与广泛采用无人机相关的风险至关重要.
- 包括传感器融合在内的多模式方法对于稳健可靠的无人机检测至关重要.
- 对新型检测技术的持续研究对于解决无人机带来的动态挑战至关重要.
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