针对噪声交叉相关的多传感器线性系统的最佳顺序融合卡尔曼波器
Weichang Huang1, Chenglin Wen2
1College of Automation, Guangdong University of Petrochemical Technology, Maoming 525000, China.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
本研究介绍了一种全球最佳的顺序融合卡尔曼波器,用于与相关噪声的多传感器线性系统. 新的过器实现了与集中融合的严格等价性,解决了状态估计中的一个长期存在的问题.
科学领域:
- 控制系统工程 控制系统工程
- 信号处理 信号处理
- 估计理论 估计理论
背景情况:
- 多传感器线性系统中的状态估计受到相关过程和测量噪声的挑战.
- 现有的序列融合卡尔曼波器对于这些系统缺乏与集中融合的严格等价性.
- 直接与过程和测量噪声无关是一个重大障碍.
研究的目的:
- 为具有交叉相关噪声的线性系统设计一个真正全球最佳的顺序融合卡尔曼波器.
- 为了实现顺序和集中融合卡尔曼波器之间的严格等价性.
- 为了解决对相互相关的测量噪声系统的顺序融合未解决的问题.
主要方法:
- 一种创新的过程和测量噪声的间接对比方法.
- 使用格拉姆-施密特直角化原理重写测量方程,以实现噪声独立.
- 建立基于转换的测量方程的顺序融合卡尔曼波器.
主要成果:
- 开发了一种新的顺序融合卡尔曼波器,实现了全球最佳性.
- 理论证明严格地确定了拟议的顺序过器和集中融合之间的等价性.
- 过器的有效性通过恒定速度目标跟踪模拟来证明.
结论:
- 提出的方法成功地设计了一个全球最佳的顺序融合卡尔曼波器,用于复杂的噪声场景.
- 已确定的等价性为状态估计提供了一个实用和高效的替代方案,而不是集中融合.
- 这项工作为多传感器系统的顺序数据融合提供了重大进展.
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