| 基于新息和残差的自适应UKF算法 |
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| 引用本文： | 周卫东,乔相伟,吉宇人,孟凡彬.基于新息和残差的自适应UKF算法[J].宇航学报,2010,31(7):1798-1804. |
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| 作者姓名： | 周卫东 乔相伟 吉宇人 孟凡彬 |
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| 作者单位： | (哈尔滨工程大学自动化学院，哈尔滨 150001) |
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| 摘 要： | 针对先验噪声统计特性与实际不符引起卡尔曼滤波精度下降的情况，提出了一种基于新息和
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| 关 键 词： | 无迹卡尔曼滤波 自适应卡尔曼滤波 协方差匹配 新息 残差 |
| 收稿时间： | 2009-09-22 |
An Innovation and Residual-Based Adaptive UKF Algorithm |
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| ZHOU Wei-dong,QIAO Xiang-wei,JI Yu-ren,MENG Fan-bin.An Innovation and Residual-Based Adaptive UKF Algorithm[J].Journal of Astronautics,2010,31(7):1798-1804. |
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| Authors: | ZHOU Wei-dong QIAO Xiang-wei JI Yu-ren MENG Fan-bin |
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| Institution: | ZHOU Wei-dong,QIAO Xiang-wei,JI Yu-ren,MENG Fan-bin(Department of Automation,Harbin Engineering University,Harbin 150001,China) |
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| Abstract: | Considering that the prior statistics noise of a Kalman filter does not agree with its real behavior,an adaptive unscented Kalman filter algorithm based on innovation and residual sequences is proposed to on-line estimate the statistics noise property. First,the observation noise covariance matrix is real-time tracked through innovation sequence. Then the real time variation of process noise covariance is on line estimated based on the orthogonal principle between innovated sequence and residual sequence es... |
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| Keywords: | Unscented Kalman filter(UKF) Adaptive Kalman filter Covariance match Innovation Residual |
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