在运动中前进-前进-后退精细对齐基于SINS/GNSS的移位观测
Yongyun Zhu1, Yaohui Zhu1, Xinhua Wei1
1School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.
Sensors (Basel, Switzerland)
|January 8, 2025
概括
一个新的前进后退算法提高了Strapdown惯性导航系统 (SINS) 初始对齐的收速度和准确性. 这种方法通过重复使用导航数据来提高性能,克服了传统卡尔曼过方法的局限性.
科学领域:
- 导航系统工程 导航系统工程
- 惯性导航 惯性导航 惯性导航
- 信号处理 信号处理
背景情况:
- 使用线性卡尔曼过的Strapdown惯性导航系统 (SINS) 的传统微细对齐算法遭受缓慢的融合.
- 这种限制阻碍了导航系统中初始对齐过程的效率和准确性.
- 为了解决这些趋同问题,需要重新分析精细调整模型.
研究的目的:
- 为SINS.提出了一种新的前进-前进-后退精细对齐算法.
- 为了提高SINS初始对齐的收速度和准确性.
- 通过模拟和车辆测试来验证拟议的算法的有效性和可行性.
主要方法:
- 在最初的导航框架中衍生出了一个前进-前进-后退的微细对齐模型.
- 利用运载机的位移向量,从全球导航卫星系统 (GNSS) 定位中获得,作为微细对齐模型的观察.
- 通过回溯和重复使用导航数据的子集,改善了初始对齐的趋同.
主要成果:
- 与传统方法相比,拟议的算法显著提高了融合速度.
- 每个回溯对齐步骤都提高了精细对齐准确度,以满足初始对齐性能要求.
- 模拟和车辆测试结果证明了回溯精细对齐算法的有效性和可行性.
结论:
- 前进后退精细对齐算法为SINS初始对齐中的缓慢收问题提供了可行的解决方案.
- 该方法的重复使用导航数据的能力有效地提高了速度和准确性.
- 这种方法在现实世界的导航系统应用中被证明是实用的.
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