基于交互式过器的自适应式集成导航算法
Bin Zhao1, Chunlei Gao2, Hui Xia1
1School of Marine and Electrical Engineering, Jiangsu Maritime Institute, Nanjing 211100, China.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
一个新的交互强大的过算法增强了无人驾驶飞行器的导航. 这种算法在具有挑战性的动态噪声环境和系统不确定性时,提高了状态估计的准确性和稳定性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 导航系统 导航系统
背景情况:
- 无人驾驶飞行器 (UAV) 的集成导航需要高精度和稳定性.
- 现有的过器在复杂的动态噪声和系统不确定性方面面临挑战.
研究的目的:
- 为无人机集成导航提出一个交互强大的过算法.
- 在不利条件下提高状态估计的准确性和稳定性.
主要方法:
- 一个集成交互式多重模型 (IMM) 概念的交互式强大的过算法.
- 强跟踪波器 (STF) 和光滑可变结构波器 (SVSF) 的互补使用与不同的模型.
- 更新波器概率和权重的概率函数,其次是输入交互和输出融合.
主要成果:
- 拟议的算法显著减少了估计错误.
- 在复杂的动态噪声和系统不确定性中,可以实现高精度的状态估计和改进的稳定性.
- 与强大的跟踪光滑过器相比,速度精度提高了16%以上,位置精度提高了40%以上.
结论:
- 交互式强大的过算法为无人机导航提供了卓越的性能.
- 它有效地解决了动态环境中的准确性和稳定性之间的权衡问题.
- 显示了与无人机应用程序的现有过技术相比的重大进步.
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