不同环境下的GPS/IMU数据融合

The GPS/IMU Integrated Navigation Based on Adaptive Fading Kalman Filter in Different Environment

为提高Kalman滤波组合导航的估计精度,在考虑系统估计误差相关的情况下,提出了采用环境背景下不同传感器的有效性概率加权GPS/IMU组合导航自适应衰减记忆滤波的融合算法。通过对各种算法进行仿真分析发现,新算法的融合估计精度高于相应的未考虑环境信息的GPS/IMU融合估计精度;新算法具有几乎和有效概率加权Kalman滤波融合算法相同的融合估计精度,但其误差变化较后者平稳。表明新算法可有效地提高系统融合估计的精度和可靠性。

In order to improve the estimated performance of the integrated navigation system, under consid- eration of the correlated estimation error, the GPS/IMU weighting fusion algorithm which based on the a- daptive fading Kalman filter is proposed. Through the simulation analysis of various algorithms, it is found that the fusion performance of the new fusion algorithm is higher than that of the algorithm without con- sidering the environmental information, and the new algorithm has hearly the same performance as the val- ue probability weighting Kalman filter algorithm, but the error of the new algorithm varied smoothly. The result of the simulation shows that the new method improved the reliability and accuracy of the multi-sensor system fusion estimation.