Low-Cost Real-Time PPP GNSS Aided INS for CAV Applications

被引:4
|
作者
Rahman, Farzana [1 ]
Silva, Felipe O. [2 ]
Jiang, Zeyi [1 ]
Farrell, Jay A. [1 ]
机构
[1] Univ Calif Riverside, Dept Elect & Comp Engn, Riverside, CA 92521 USA
[2] Univ Fed Lavras, Dept Automat, BR-37200900 Lavras, Brazil
关键词
Connected and autonomous vehicles; global navigation satellite systems; precise point positioning; inertial navigation; state estimation; INERTIAL NAVIGATION; VEHICLE NAVIGATION; TIGHT INTEGRATION; CODE BIASES; GPS; SYSTEM; FILTER;
D O I
10.1109/TITS.2022.3208849
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Many connected and autonomous vehicle (CAV) applications benefit from navigation technologies that reliably achieve lane-level accuracy. Global organizations have recently begun to provide real-time common-mode error corrections for Global Navigation Satellite Systems (GNSS) that enable this level of positioning accuracy using Precise Point Positioning (PPP). Incorporating an Inertial Measurement Unit (IMU) with a GNSS receiver can achieve this positioning performance reliably on moving platforms while providing a full state estimate, with high bandwidth at a high sampling rate. For commercial automotive applications cost is critical; therefore, this article focuses on commercial grade IMU's and single-frequency GNSS code and Doppler measurements. This article presents and demonstrates a tightly-coupled PPP GNSS aided Inertial Navigation System (INS) using only publicly available real-time data sources. The article discusses the role of the INS in automotive applications and how the quality of the IMU affects the ability to achieve that role. The experimental results demonstrate positioning accuracy that surpasses the Society of Automotive Engineering (SAE) J2945 specification (horizontal error <= 1.5 m and vertical error <= 3 m 68%).
引用
收藏
页码:25018 / 25032
页数:15
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