自适应联邦滤波器在GPS-INS-Odometer组合导航的应用

针对多传感器观测信息较多、计算效率较低、对动力学模型误差稳键性不佳的问题,提出了一种自适应联邦滤波器并应用于GPS-INS-Odometer组合导航。首先介绍GPS-INS-Odometer组合导航的动力学模型和观测模型,比较分析了信息分配因子和自适应因子的共同特性,论证了联邦滤波器和自适应滤波器的等价性及其等价成立条件,提出了自适应联邦滤波器的信息分配因子构造方法。最后利用实测数据验证了算法的有效性。结果表明,相比于基于GPS和Odometer(里程计)初始方差构造信息分配因子的联邦滤波器,本文提出的自适应联邦滤波器兼容了联邦滤波器高效计算效率,且具有较好的抵抗动力学模型误差效果,能够有效削弱多传感器动力学模型误差对于导航解算的影响,对直接可测参数和间接可测参数的精度提高均起到了积极的作用。

The Application of Adaptive Federated Filter in GPS-INS-Odometer Integrated Navigation

In multi-sensor integrated navigation,extensive observation information,low computational efficiency and weak robust ability will lead to poor navigation performance.An adaptive federated filter is proposed and applied in GPS-INS-Odometer integrated navigation.First the dynamical model and observation model of GPS-INS-Odometer integrated navigation are introduced.Information allocation factor and adaptive factor are compared to find out their common characteristic.The equivalence property between federated filter and adaptive filter is proved and the condition of equivalence is built.The information allocation factor of adaptive federated filter is constructed.Finally an actual calculation was performed to test the validity of new algorithm.The results of the experiment indicate that compared with the information allocation factor constructed by initial variance of GPS and Odometer in classical federated filter,adaptive federated filter shows well robust performance and high computational efficiency.It can weaken the influence of multi-sensor dynamical modeldisturbance on navigation resolution.The proposed method plays a positive role in improving the accuracy of directly measurable parameters and indirectly measurable parameters.