| 崔冰波,吉 峰,孙 宇,魏新华.高斯过程改进的鲁棒容积卡尔曼滤波
及其组合导航应用[J].电子测量与仪器学报,2021,35(9):34-40 |
| 高斯过程改进的鲁棒容积卡尔曼滤波
及其组合导航应用 |
| Gaussian process enhanced robust cubature kalman filter andapplication in integrated navigation |
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| DOI： |
| 中文关键词: 组合导航 容积卡尔曼滤波 高斯过程 状态可观测度 |
| 英文关键词:integrated navigation cubature Kalman filter Gaussian process state observability |
| 基金项目:国家自然科学基金(31901416)、江苏省自然科学基金(BK20180859)、中国博士后科学基金(2019M651745)项目资助 |
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| 中文摘要: |
| 基于 GNSS / INS 的导航状态估计受状态可观测度影响较大,为提高陆地载体航向角的估计精度,提出了一种改进鲁棒
容积卡尔曼滤波(RCKF)方法。 首先采用免重采样采样点更新框架实现容积点更新与高斯矩信息的解耦,提高采样点实例化
信息在迭代滤波中的传播效率。 其次基于状态可观测度分析,将高斯过程(GP)引入到系统模型矩估计积分不确定性的标定
中,改善移动载体直线行驶条件下航向的估计精度。 仿真实验表明,所提 GP-RCKF 算法能在状态可观测度较弱时显著改善航
向角估计精度,航向角误差较 RCKF 改善 28. 9%。 |
| 英文摘要: |
| The observable degree of navigation state has a significant effect on the state estimation of GNSS / INS. In order to improve the
accuracy of heading of land vehicle, an improved robust cubature Kalman filter (RCKF) method is proposed. First, the resampling-free
sigma-point update framework is employed to separate the cubature point update from the Gaussian information limitation, so that improve
the propagation efficiency of the information contained in instantiated points in the iteratively filtering period. Secondly, in order to
improve the heading of land vehicle when it travels along a straight-line, the Gaussian process (GP) is introduced into the uncertainty
calibration of moment approximation of system model based on state observability analysis. Simulation results indicate that GP-RCKF
improves the heading angle obviously when the state observability is weak, and compared with RCKF the heading is improved by 28. 9%. |
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