Abstract: In this paper, a newly developed adaptive fuzzy Kalman filter algorithm is analyzed, and proposed to replace the conventional Kalman filtering approach for the inertial navigation system (INS)/ Global Positioning System (GPS) integrated system. the system noise covariance matrix(Q). and the measurement noise covariance matrix(R) is modified “online” by the fuzzy logic controller and to improve the positioning accuracy of the integrated navigation system. Simulation results show that the proposed algorithm can improve the performance(accuracy and reliability) of the integrated GPS/INS system filtering process .

摘要： 现代导航和制导系统,对导航的精度越来越要求高,相应的应用环境日趋复杂,对噪声统计特性的描述也越来越困难,而传统的卡尔曼滤波过程依赖于系统过程和测量过程的数学模型和其统计模型的正确性.这将造成滤波器的不稳定,本文总结了常用的自适应滤波的方法,并提出一种基于模糊逻辑的自适应卡尔曼滤波技术，用模糊逻辑自适应推理器来“在线”修正卡尔曼滤波系统噪声协方差Q和测量噪声协方差（R），从而使滤波器不断执行最优估计。仿真结果表明此方法可以提高GPS/INS组合导航系统的精度和可靠性。