一个卡尔曼过算法测量中断基于多项式插值和泰勒扩展.
Jianhua Cheng1, Zili Wang1, Bing Qi1
1College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China.
Entropy (Basel, Switzerland)
|March 28, 2024
概括
这项研究引入了一个自适应的卡尔曼过算法,以提高在GPS信号丢失时的导航准确性. 该方法提高了SINS/GPS系统组合的态度,速度和位置估计的准确性.
科学领域:
- 导航系统工程 导航系统工程
- 信号处理 信号处理
- 控制理论 控制理论
背景情况:
- 联合Strapdown惯性导航系统 (SINS) 和全球定位系统 (GPS) 导航系统被广泛使用,但在城市峡谷,道和树叶下遭受GPS信号阻塞.
- GPS信号中断导致SINS/GPS系统退化为纯惯性导航,导致大量累积错误.
研究的目的:
- 提出一种自适应的卡尔曼过算法,以减轻SINS/GPS系统中GPS信号中断引起的导航错误.
- 在GPS信号暂时不可用时,提高导航解决方案的准确性和稳定性.
主要方法:
- 开发了一个自适应的卡尔曼过算法,结合了多项式拟合和泰勒扩展.
- 利用惯性引导系统数据进行多项式插值,在GPS中断期间构建虚拟速度和位置测量.
- 采用泰勒扩展来创建虚拟测量,弥补GPS数据的缺乏.
主要成果:
- 计算机模拟和道路测试表明,与没有救援措施的标准算法相比,性能有所改善.
- 拟议的算法显著提高了立场角度估计的准确性.
- 该算法还提高了速度估计精度和位置定位精度.
- 在GPS信号中断期间,系统的整体稳定性更高.
结论:
- 拟议的自适应卡尔曼过算法有效地弥补了SINS/GPS导航组合中的GPS信号损失.
- 这种方法显著提高了导航准确性和系统稳定性在具有挑战性的环境.
- 该技术提供了一个强大的解决方案,可以在GPS间歇性无法使用时保持可靠的导航性能.
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