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对于经历日食的立方卫星的态度确定系统
Kesaobaka Mmopelwa1, Teddy Tumisang Ramodimo1, Oduetse Matsebe1
1Department of Mechanical, Energy, and Industrial Engineering, Fauculty of Engineering, Botswana International University of Science and Technology, Private Bag 16, Palapye 10071, Botswana.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
本研究引入了适应式扩展卡尔曼波器用于立方卫星态度估计,通过动态调整不确定性矩阵来提高准确性. 这种新的方法在不同的轨道条件下提高了可靠性.
科学领域:
- 航空航天工程 航空航天工程
- 控制系统 控制系统
- 信号处理 信号处理
背景情况:
- 卡尔曼波器依赖预测误差共变率 (Pk+1) 和测量噪声 (R) 矩阵来模拟不确定性.
- 这些矩阵在现实场景中可能变得不准确,例如由于测量错误导致的立方体卫星任务.
- 准确的态度估计对于立方卫星运行和任务成功至关重要.
研究的目的:
- 开发一个适应性扩展卡尔曼波器用于立方卫星的态度估计.
- 动态估计预测错误共变矩阵 (Pk+1) 和测量噪声共变矩阵 (R).
- 为了提高方位估计的准确性,特别是在具有挑战性的轨道条件下.
主要方法:
- 实现一个自适应扩展卡尔曼波器 (AEKF).
- 使用预期最大化 (EM) 算法进行动态矩阵估计.
- 进行模拟实验以验证AEKF的性能.
主要成果:
- 与现有方法相比,拟议的AEKF显示出优越的态度估计准确性.
- 在日照和阴影的轨道阶段,性能改善尤其显著.
- 该算法在相同的过参数和初始条件下实现了更高的准确性.
结论:
- 适应式扩展卡尔曼波器有效地解决了CubeSat态度估计中的时间变化的不确定性.
- 使用EM方法对Pk+1和R的动态估计可以提高过器的稳定性.
- 这种方法为可靠的立方卫星态度确定提供了显著的进步.
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