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基于数值研究的新型集成惯性导航系统与单轴冷原子干扰仪陀螺仪
Zihao Chen1, Fangjun Qin1, Sibin Lu2
1College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China.
Micromachines
|August 28, 2025
概括
这项研究将冷原子干扰仪陀螺仪 (CAIG) 与常规惯性测量单元 (IMU) 集成,以改善导航. 这种新系统在24小时内显著减少了导航错误.
科学领域:
- 导航系统工程
- 量子传感技术
- 控制系统理论
背景情况:
- 惯性导航系统 (INS) 提供自主,隐蔽,长时间的操作,但随着时间的推移会累积错误.
- 传感器的局限性和操作原理导致传统INS的累积错误.
- 准确的导航对于各种应用至关重要,需要错误缓解策略.
研究的目的:
- 理论上探索和数值模拟一个集成的惯性导航系统,结合冷原子干扰仪陀螺仪 (CAIG) 和传统的惯性测量单元 (IMU).
- 利用CAIG (低偏差,漂移) 和IMU (高采样率) 的明显优势提高导航准确度.
- 开发和实施适应梯度上升 (AGA) 方法,以在线估计卡尔曼波器中的测量噪声差异.
主要方法:
- 单轴冷原子干扰仪陀螺仪 (CAIG) 与常规惯性测量单元 (IMU) 的集成.
- 在线卡尔曼波器参数调节的自适应梯度上升 (AGA) 算法的开发.
- 整合系统在24小时运行期间的数值模拟.
主要成果:
- 与传统的IMU相比,集成系统显著减少了导航错误.
- 在24小时内,度,经度和定位错误分别减少了43. 9%,32. 6%和32. 3%.
- 在线卡尔曼波器有效地减少了来自惯性传感器漂移的错误.
结论:
- 拟议的综合惯性导航系统,结合CAIG和IMU,提供卓越的导航精度.
- 通过精确估计噪声差异,自适应梯度上升方法提高了卡尔曼波器的性能.
- 这种方法为缓解长期自主导航的累积错误提供了可行的解决方案.
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