自适应联邦滤波器在GPS-INS-Odometer组合导航的应用

发布时间：2018-04-29 22:10

本文选题：GPS-INS-Odometer组合导航 + 联邦滤波器　；参考：《测绘学报》2016年02期

【摘要】：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。
[Abstract]:An adaptive federated filter is proposed to solve the problem of low computational efficiency and poor stability of dynamic model error. An adaptive federated filter is proposed and applied to GPS-INS-Odometer integrated navigation. Firstly, the dynamic model and observation model of GPS-INS-Odometer integrated navigation are introduced, the common characteristics of information allocation factor and adaptive factor are compared and analyzed, and the equivalence of federated filter and adaptive filter is proved. An information allocation factor construction method for adaptive federated filters is proposed. Finally, the validity of the algorithm is verified by the measured data. The results show that the proposed adaptive federated filter is compatible with the efficient computation efficiency of the federated filter, compared with the federated filter based on the initial variance of GPS and odometer. It can effectively weaken the influence of multi-sensor dynamic model error on navigation solution and improve the accuracy of direct and indirect measurable parameters.
【作者单位】：中国矿业大学国土环境与灾害监测国家测绘地理信息局重点实验室;中国矿业大学环境与测绘学院;
【基金】：国家863计划(2013AA12A201) 江苏高校优势学科建设工程(SZBF2011-6-B35) 高等学校博士学科点专项科研基金(20130095110022)~~
【分类号】：P228.4

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