在高动态遭遇场景中对无人机目标进行静电传感的建模和验证
Rongxiang Xia1, Huifa Shi1, Shaojie Ma1
1School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Sensors (Basel, Switzerland)
|August 28, 2025
概括
这项研究引入了用于检测无人驾驶飞行器 (UAV) 的静电传感器的新模型. 该模型准确地预测传感器信号,改善无人机检测和拦截能力.
科学领域:
- 电气工程
- 航空航天工程
- 传感器技术
背景情况:
- 无人驾驶飞行器 (UAV) 存在越来越多的公共安全风险,因为它们可能被滥用.
- 静电传感器提供了一种通过分析静电信号来检测无人机的方法.
- 由于参数合,对静电传感器信号的准确建模具有挑战性.
研究的目的:
- 开发一个分析模型来预测无人机遇到的静电传感器信号.
- 为了考虑碰撞参数和传感器电路特征之间的复杂相互作用.
- 提高无人机检测和拦截的静电传感系统的有效性.
主要方法:
- 提出了对电流浮动静电传感器信号的分析建模方法.
- 在实际边界条件下校准模型,包括碰撞角度,失误距离和相对速度.
- 通过在动态碰撞中获取静电信号的空中数据来验证模型.
主要成果:
- 开发的模型准确地预测了多变量合下的静电传感器信号.
- 预测信号与测量数据具有很高的相关性 (系数> 0.9).
- 该模型表现出显著的计算效率.
结论:
- 拟议的分析模型有效地预测无人机检测的静电传感器信号.
- 该模型的精度和效率支持无人机拦截系统的设计和优化.
- 这项研究促进了低空无人机安全的静电传感应用.
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