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Optimized fast desensitized Kalman filter

delete2026-06-25
delete0
PRE
AI
T
Taishan Lou
L
Liang Ma *
L
Li-Ying Jiang
Y
Yu-zhao Jiao
L
Liang-Yu Zhao
R
Renlong Qi *
DOI：10.1016/j.asr.2026.06.075delete
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摘要

摘要

En 中文
基于PSO的优化快速去敏卡尔曼滤波器（OFDKF）和优化快速去敏扩展卡尔曼滤波器（OFDEKF）为线性及非线性系统参数不确定性问题提供了创新解决方案。该方法通过设计缩放因子调整灵敏度加权矩阵，并利用粒子群优化算法（PSO）中的适应度函数最小化过程获取最优值。仿真验证了所提OFDKF/OFDEKF算法在三种参数不确定性场景下，相比传统方法显著提高了线性与非线性系统的估计精度和鲁棒性。
Keyword:
Optimized fast desensitized Kalman filter
Uncertain parameters
Sensitivity-weighting matrix
Particle swarm optimization

期刊

Advances in Space Research 封面图
Advances in Space Research
IF:
2.8
论文数:
1.8K
被引数:
2.0W

机构

A
aerospace information technology university
学者数:
88
论文数: 75
被引数: 0
Z
zhengzhou university of light industry
学者数:
1.5K
论文数: 429
被引数: 0
B
beijing institute of technology
学者数:
5.5W
论文数: 4.0W
被引数: 63
Z
Zhengzhou University of Science and Technology
学者数:
81
论文数: 46
被引数: 169
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