| 摘要: |
| 传统的无迹Kalman滤波根据估计量测方程和量测量的协方差矩阵来确定最佳增益，但在导航过程中会因为外界因素的干扰，无法得到准确的量测信息算法，使增益有所偏差，导致最后的滤波精度降低。基于此，提出了一种改进的无迹Kalman滤波。首先根据新息，判断是否有异常的观测量，并通过引入抗差因子进行修正。通过仿真实验，比较扩展Kalman滤波、无迹Kalman滤波和改进的无迹Kalman滤波的误差特性，证明提出算法的有效性。 |
| 关键词: 无迹Kalman滤波 新息 抗差因子 量测信息 |
| DOI： |
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| 基金项目: |
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| An Improved Unscented Kalman Filter for SINS/GPS Integrated Navigation |
| CHEN Guotong,FAN Yuanyuan,LIU Qi |
| (College of Information Science and Engineering, Hebei University of Science and Technology) |
| Abstract: |
| The traditional unscented Kalman filter（UKF） determines the optimal gain based on the estimated measurement equation and the covariance matrix of the quantity measurement. However, in the navigation process, due to the interference of external factors, accurate measurement information cannot be obtained, resulting in gain. The deviation causes the final filtering accuracy to decrease. Based on this, an improved unscented Kalman filter is proposed in this paper. Firstly, based on the new interest, it is judged whether there is an abnormal observation, and this is corrected by introducing a resistance factor. Through the simulation experiments, the error characteristics of extended Kalman filter（EKF), unscented Kalman filter and improved unscented Kalman filter are compared, and the effectiveness of the proposed algorithm is proved. |
| Key words: Unscented Kalman filter（UKF) Innovation Resistance factor Measurement information |