摘要
针对具有不确定动态模型参数的GPS/INS组合导航系统,基于传统Kalman滤波器之上,介绍了一种模糊自适应Kalman滤波器,讨论了GPS/INS组合系统中模型参数不确定性的问题,给出了一种利用模糊自适应滤波方法进行数据融合的无人机定位误差修正方法;仿真结果表明,模糊自适应卡尔曼滤波器对非线性GPS/INS组合系统是很有效的,提高了定位精度。
The nonlinear GPS/ INS integration with uncertain dynamics modelling is discussed. On the basis of traditional Kalman filter, a fuzzy adaptive Kalman filter is described. Uncertain dynamics modeling of an integrated GPS/INS system is discussed. Data fusion of UVA＇s position error correction based on this fuzzy adaptive filter is showed. Simulation result presents fuzzy adaptive Kalman filter is very efficient for nonlinear GPS/INS integration system. The accuracy is enhanced. Values estimated by data fusion based on fuzzy adaptive Kalman filter are very close to real values.
出处
《计算机测量与控制》
CSCD
2006年第11期1529-1530,1559,共3页
Computer Measurement &Control
