无人机控制器本地化基于RSSI比率
Yuhong Wang1, Yonghong Zeng1, Sumei Sun1
1Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore 138632, Singapore.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
我们开发了两种无人机控制器本地化方法,使用接收信号强度指标 (RSSI) 的比率. 这些方法在模拟和实地试验中优于现有的算法,提高了无人机跟踪的准确性.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 无线通信和网络无线通信和网络.
- 信号处理 信号处理
背景情况:
- 无人机控制器的准确定位对于安全高效的操作至关重要.
- 现有的本地化方法在复杂的无线环境中可能面临挑战.
- 接收信号强度指标 (RSSI) 的比率为本地化提供了一个潜在的途径.
研究的目的:
- 建议和评估使用RSSI比率用于无人机控制器本地化的新方法.
- 将拟议方法的性能与现有的算法进行比较.
- 研究环境因素和系统参数对定位准确性的影响.
主要方法:
- 开发了两个基于RSSI比率的本地化算法:指纹和基于模型的.
- 在各种通道条件下 (WLAN,TRGR) 进行广泛的模拟.
- 执行现实世界的实地试验,以验证模拟结果.
主要成果:
- 拟议的RSSI比率方法在WLAN道中的距离映射算法相比显示出更高的性能.
- 增加了传感器数量和RSSI比率样本的平均值,改善了定位准确性,特别是在非色通道中.
- 网格尺寸的缩小在低阴影场景中提高了性能,在高阴影场景中降低了回报.
结论:
- 拟议的RSSI比率指纹和基于模型的算法为无人机控制器本地化提供了强大的和有效的解决方案.
- 定位精度受到传感器数量,信号平均值和通道特征的影响.
- 实地试验结果证实了模拟结果,证实了这些方法的实际适用性.
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