测绘学报 ›› 2024, Vol. 53 ›› Issue (3): 425-434.doi: 10.11947/j.AGCS.2024.20220349
穆梦雪1,2, 赵龙1,2,3
收稿日期:
2022-05-24
修回日期:
2023-12-30
发布日期:
2024-04-08
通讯作者:
赵龙
E-mail:buaa_dnc@buaa.edu.cn
作者简介:
穆梦雪(1993—),女,博士生,研究方向为多源信息融合定位导航。E-mail:Mumengxue@buaa.edu.cn
基金资助:
MU Mengxue1,2, ZHAO Long1,2,3
Received:
2022-05-24
Revised:
2023-12-30
Published:
2024-04-08
Supported by:
摘要: 为提升复杂环境下低成本车载导航系统的容错性能,本文研究了基于次优增益融合(SGF)算法的GNSS/SINS/里程计分布式弹性融合方法。该方法首先根据阿克曼转向几何建立了四轮里程计测速补偿模型,提升了惯性测量单元(IMU)安装中心处的前向和侧向测速精度;然后设计了基于卡方检验统计量的故障检测与分类准则,充分利用了可获取的观测信息;最后构建了随机模型和信息分配因子(ISF)弹性优化模型,分别从传感器层和决策层减少了异常观测的影响,实现了车载多源信息的弹性融合。通过实际跑车数据对GNSS/SINS/里程计分布式弹性融合方法进行测试验证。试验结果表明,本文方法能有效减少子系统故障对全局状态估计的影响,提升复杂环境下系统的容错性能。此外,与经典的联邦卡尔曼滤波(FKF)算法相比,SGF算法全局融合精度损失有限,计算效率却显著提升,有利于多源信息弹性融合的实际工程应用。
中图分类号:
穆梦雪, 赵龙. 车载GNSS/SINS/里程计分布式弹性融合导航方法[J]. 测绘学报, 2024, 53(3): 425-434.
MU Mengxue, ZHAO Long. A distributed GNSS/SINS/odometer resilient fusion navigation method for land vehicle[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(3): 425-434.
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