中文摘要：

针对常规联邦卡尔曼滤波需要确切已知系统噪声统计特性的局限性，结合多信息组合导航中惯性导航系统噪声难以确切感知和卫星导航系统测量噪声不断变化的特点，提出了一种新的双重自适应联邦滤波算法。该算法不必知道系统噪声统计特性而能对测量噪声进行在线自适应调节，同时信息分配系数根据各卫星导航系统输出的几何精度因子（GDOP）进行自适应调节。通过SINS-GPS-Galileo．北斗组合导航系统将该算法与常规联邦滤波算法进行仿真比较，结果表明：该方法有效提高了组合导航系统的精度和可靠性，更适用于系统噪声未知和测量噪声不断变化的多信息组合导航系统。

英文摘要：

A new double-adaptive federated filter is put forward in order to get rid of the disadvantage of general federated Kalman filter that the statistic characteristics of the noise must be known exactly. Considering in multiinformation integrated navigation in which the systematic noise of inertial navigation system is not known exactly and the measurement noise of satellite-navigation is time-varying, the new algorithm does not need to know the statistic characteristics of systematic noise and can adjust the measurement noise on-line, meanwhile, the information distribution coefficient can be adaptive adjusted according to the geometry dilution of precision （GDOP） ,which is the real-time output of the satellite-navigation. In SINS-GPS-Galileo-BDS integrated navigation system,the simulation results which compared with general federated filter show that this method effectively improves the integrated navigation＇ s precision and reliability, and more applicable for the multi-information integrated navigation system which systematic noise is unknown and measurement noise is time-varying.