GPS/INS
快速卡尔曼滤波
不变扩展卡尔曼滤波器
大地测量学
卡尔曼滤波器
全球定位系统
控制理论(社会学)
α-β滤光片
自适应滤波器
扩展卡尔曼滤波器
计算机科学
集合卡尔曼滤波器
噪音(视频)
核自适应滤波器
协方差矩阵
GPS信号
惯性导航系统
滤波器(信号处理)
算法
全球导航卫星系统应用
数学
地质学
辅助全球定位系统
滤波器设计
人工智能
计算机视觉
移动视界估计
电信
方向(向量空间)
几何学
控制(管理)
图像(数学)
作者
Ashraf A. Mohamed,K. P. Schwarz
标识
DOI:10.1007/s001900050236
摘要
After reviewing the two main approaches of adaptive Kalman filtering, namely, innovation-based adaptive estimation (IAE) and multiple-model-based adaptive estimation (MMAE), the detailed development of an innovation-based adaptive Kalman filter for an integrated inertial navigation system/global positioning system (INS/GPS) is given. The developed adaptive Kalman filter is based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors. Results from two kinematic field tests in which the INS/GPS was compared to highly precise reference data are presented. Results show that the adaptive Kalman filter outperforms the conventional Kalman filter by tuning either the system noise variance–covariance (V–C) matrix `Q' or the update measurement noise V–C matrix `R' or both of them.
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