惯性测量装置
航位推算
卡尔曼滤波器
惯性导航系统
加速度计
导航系统
全球导航卫星系统应用
GPS信号
传感器融合
扩展卡尔曼滤波器
人工智能
作者
Sheng Zhao,Yiming Chen,Jay A. Farrell
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2016-10-01
卷期号:17 (10): 2854-2867
被引量:40
标识
DOI:10.1109/tits.2016.2529000
摘要
Many applications demand high-precision navigation in urban environments. Two frequency real-time kinematic (RTK) Global Positioning System (GPS) receivers are too expensive for low-cost or consumer-grade projects. As single-frequency GPS receivers are getting less expensive and more capable, more people are utilizing single-frequency RTK GPS techniques to achieve high accuracy in such applications. However, compared with dual-frequency receivers, it is much more difficult to resolve the integer ambiguity vector using single-frequency phase measurements and therefore more difficult to achieve reliable high-precision navigation. This paper presents a real-time sliding-window estimator that tightly integrates differential GPS and an inertial measurement unit to achieve reliable high-precision navigation performance in GPS-challenged urban environments using low-cost single-frequency GPS receivers. Moreover, this paper proposes a novel method to utilize the phase measurements, without resolving the integer ambiguity vector. Experimental results demonstrate real-time position estimation performance at the decimeter level. Furthermore, the novel use of phase measurements improves the robustness of the estimator to pseudorange multipath error.
科研通智能强力驱动
Strongly Powered by AbleSci AI