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建立了车载ＧＰＳ（ＧｌｏｂａｌＰｏｓｉｔｉｏｎｉｎｇＳｙｓｔｅｍ）／ＤＲ（ＤｅａｄＲｅｃｋｏｎｉｎｇ）组合导航系统自适应扩展卡尔曼滤波模型及其算法，从而大大提高了车辆导航系统的定位精度．首次提出依据ＰＤＯＰ（位置误差系数）等ＧＰＳ定位系统的输出参数，自动调整观测噪声协方差阵Ｒ和系统噪声协方差阵Ｑ的大小，从而自适应地调整组合导航系统模型性能的方法，使得模型具有较强的适应性．计算机仿真及实验结果表明应用该模型具有良好的效果．
A self-adaptive extended Kalman filter model and its algorithm for integrated GPS (Global Positioning System) / DR (DR) navigation system are established, which greatly improves the positioning accuracy of the vehicle navigation system. The method of adaptively adjusting the performance of integrated navigation system model is proposed based on the output parameters of GPS positioning system such as PDOP (Position Error Coefficient) and automatically adjusting the covariance matrix R of observation noise and the system noise covariance matrix Q, Has strong adaptability. Computer simulation and experimental results show that the model has good effect.