基于移动开窗法协方差估计和方差分量估计的自适应滤波

基金项目: 国家杰出青年基金资助项目(49825107);国家自然科学基金资助项目(40174009,40274002)

详细信息

An Adaptive Kalman Filter Combining Variance Component Estimation with Covariance Matrix Estimation Based on Moving Window

Xi'an Research Institute of Surveying and Mapping, 1 Mid-Yanta Road, Xi'an, China, 710054

摘要: 基于移动窗口协方差估计和方差分量估计,提出了一种新的自适应Kalman滤波技术。计算结果证实,该方法能有效地控制观测异常和载体状态扰动异常对动态系统参数估值的影响。
- 移动窗口协方差估计 /
- 自适应估计 /
- 抗差估计 /
- 方差分量估计
Abstract: An adaptive filtering based on moving window covariance estimation is introduced after the shortcomings of covariance matrices formed by windowing residual vectors,innovation vectors and correction vectors of the dynamic states are analyzed.A new adaptive Kalman filter is developed by combining the moving window covariance and the variance component estimation.It shows that the new adaptive filtering is not only simple in calculation but also robust in controlling the measurement outliers and kinematic state disturbance.
- moving window covariance estimation /
- adaptive estimation /
- robust estimation /
- variance components