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根据恒星图像的光学流量估计航天器的角度速度,使用优化的卡尔曼波器
Jiaqian Si1, Yanxiong Niu1, Haisha Niu2
1School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191, China.
Biomimetics (Basel, Switzerland)
|December 27, 2024
概括
本研究介绍了一种优化的卡尔曼过方法,使用恒星图像光流来估计航天器的角速度. 这种新的方法提高了动态条件下的准确性和适应性,优于传统方法.
科学领域:
- 生物模拟视觉是生物模拟视觉.
- 太空船的导航和定位定位.
背景情况:
- 光流对于导航和感知至关重要,模仿生物视觉.
- 恒星传感器为航天器态度测量提供关键的光流数据.
- 准确的角速度估计对于在复杂环境中运行的航天器至关重要.
研究的目的:
- 提出一个优化的卡尔曼选方法,用于使用恒星图像光学流来估计航天器的角度速度.
- 在动态条件下提高角度速度估计的适应性和准确性.
主要方法:
- 从连续的恒星图像中获得的利用光学流.
- 开发了一种优化的卡尔曼过算法,其中包含了适应因子.
- 通过模拟,将拟议的方法与经典的卡尔曼过方法进行了比较.
主要成果:
- 提出的优化卡尔曼选方法显示了高精度.
- 该方法表现出强大的性能,特别是在动态条件下.
- 这种方法只需要从两个连续的恒星图像中获得光学流.
结论:
- 优化的卡尔曼过方法为航天器角速度估计提供了显著的改进.
- 适应因素提高了该方法在动态空间环境中的有效性.
- 这种技术提供了精确可靠的解决方案,用于使用恒星传感器确定位置.
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