一种改进的低成本车载MIMU/GPS组合导航系统算法  

A Better Low-Cost MIMU/GPS Integrated Navigation Algorithm for Land Vehicle

作　　者：阮晓明[1] 程咏梅[1] 程承[1] 潘泉[1] 

机构地区：[1]西北工业大学自动化学院,陕西西安710072

出　　处：《西北工业大学学报》2012年第6期952-956,共5页Journal of Northwestern Polytechnical University

基　　金：航空科学基金(20090853013;20100853010)资助

摘　　要：针对低成本车载MIMU/GPS组合导航系统中存在的航向角可观测性较弱的问题,建立了一种加入GPS测速所获得的航向角信息的量测方程,增强系统航向角的可观测性,从而解决了低成本车载MIMU/GPS组合导航中的航向角可观测性较弱的问题。同时,为提高实时计算效率,并考虑低精度惯性器件噪声统计特性不易准确获得,采用降阶状态模型,并设计改进型强跟踪卡尔曼滤波与U-D分解相结合的滤波算法来抑制模型不精确造成的滤波发散。跑车实验表明,所设计的方法能够很好适用于低成本车载MIMU/GPS组合导航系统。Sections 1 though 4 of the full paper explain our algorithm mentioned in the title, which we believe is better than existing ones. Their core consists of： （ 1 ） due to the problem of weak observability of yaw angle in Chi- nese low-cost MIMU/GPS integrated navigation for land vehicle, we put forward a new measurement equation adding the information of yaw angle determined from GPS velocity, which enhances the observability of yaw angle and solves the problem; MINU stands for Miniature Inertial Measurement Unit and GPS stands for Global Positio- ning System; （2） for improving the efficiency of real-time calculations and considering hard-to-obtain statistical properties of low-precision inertial devices, we adopt reduced order state model; （3） our filter algorithm, which combines that of the modified strong tracking Kalman filter with that of the UD decomposition filter, is designed to suppress the filter divergence cause of imprecise model. The experimental results, presented in Figs. 2 through 7 and Table 1, and their analysis show preliminarily that our algorithm is indeed better for the low-cost MIMU/GPS integrated navigation system for land vehicle.

关 键 词：MIMU GPS组合导航 航向角 改进型强跟踪卡尔曼滤波 U-D分解滤波 

分 类 号：V249.32[航空宇航科学与技术—飞行器设计] TP391.9[自动化与计算机技术—计算机应用技术]