噪声协方差矩阵加权估计的Sage自适应滤波

介绍了经典 Kalm an滤波和目前广泛使用的 Sage自适应滤波 ,分析了基于新息向量、残差向量和状态改正数向量的自适应协方差估计存在的问题 ,提出了一种改进 Sage自适应滤波的新方法。计算结果表明 ,该方法能有效地控制观测异常和动态扰动异常对噪声协方差估计的影响 ,在高动态 GPS数据处理中具有较强的数值稳定性和自适应性。

Sage Adaptive Filtering with the Weighted Prediction of the Variance-covariance Matrix

After a brief review of classical Kalman filtering and Sage adaptive filtering, the drawbacks of estimating variance covariance are analyzed on the basis of the residual vectors, innovation vectors and correction vectors of predicted state. A newly improved Sage adaptive filtering algorithm is introduced to estimate the variance covariance matrix of noises. Test results show that the proposed algorithm is not only effective in controlling the measurement outliers and kinematic state disturbing but also of good stability and adaptability in the kinematic GPS data processing.