Research on GNSS INS & GNSS/INS Integrated Navigation Method for Autonomous Vehicles: A Survey

被引:8
|
作者
He, Yuan [1 ]
Li, Jichuan [2 ]
Liu, Junjie [3 ]
机构
[1] Anhui Agr Univ, Sch Nat Sci, Hefei 230036, Peoples R China
[2] Beijing Inst Remote Sensing Equipment, Lab Sci & Technol Millimeter Wave, Beijing 100854, Peoples R China
[3] Beijing Inst Remote Sensing Equipment, Lab Millimeter Wave, Beijing 100854, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous vehicles; Global Navigation Satellite System; inertial navigation system; GNSS/INS integrated navigation; MULTI-GNSS; PERFORMANCE ENHANCEMENT; KALMAN FILTER; SYSTEM; MODEL; PPP; ALGORITHM; INTEGRITY; CARS;
D O I
10.1109/ACCESS.2023.3299290
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Autonomous Vehicles have become the focus of research around the world. Meanwhile, the continuous development of various emerging technologies in recent years has paved the way for the realization of fully autonomous driving. Furthermore, high-precision navigation and positioning systems are crucial to self-driving cars. For navigation and positioning technology of autonomous vehicles, Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated navigation is of great significance to realizing high-precision navigation and positioning of autonomous vehicles. This paper researches and summarizes the development and current situation of GNSS, INS, and GNSS/INS integrated navigation technology. GNSS/INS integrated navigation algorithms are divided into four different models of combination methods: Ultra tightly Coupled, Tightly Coupled, Semi-tightly Coupled, and Loosely Coupled. Besides, the advantages and disadvantages of these four integrated navigation algorithms are compared and discussed. The characteristics of different GNSS/INS coupling models are summarized in the last chapter, and the potential research direction of GNSS/INS in the future is proposed.
引用
收藏
页码:79033 / 79055
页数:23
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