4.8 Article

Tightly Coupled Integration of GNSS, INS, and LiDAR for Vehicle Navigation in Urban Environments

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 9, Issue 24, Pages 24721-24735

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3194544

Keywords

Global navigation satellite system (GNSS); inertial navigation system (INS); light detection and ranging (LiDAR); tightly coupled integration; vehicle navigation

Funding

  1. National Key Research and Development Program of China [2021YFB2501102]

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The demand for high-precision positioning and navigation in emerging IoT applications is increasing. The limitations of the global navigation satellite system (GNSS) in urban areas and the accuracy issues of inertial navigation system (INS) with low-cost microelectromechanical system (MEMS) inertial measurement units (IMUs) have led to the proposal of a tightly coupled multi-GNSS PPP/INS/LiDAR integrated system. This integrated system, along with the LiDAR sliding-window plane-feature tracking method, has been proven to provide submeter level horizontal positioning accuracy in challenging GNSS environments with significant improvements compared to traditional GNSS/INS integration.
The emerging Internet of Things (IoT) applications, such as driverless cars, have a growing demand for high-precision positioning and navigation. Nowadays, the global navigation satellite system (GNSS) is recognized as an important approach for worldwide positioning services. However, its application is limited in urban areas due to severe signal attenuation, reflections, and blockages. Inertial navigation system (INS) can provide high-precision navigation outputs within a short period, but its accuracy suffers from error accumulation, especially when equipped with the low-cost microelectromechanical system (MEMS) inertial measurement units (IMUs). In addition, light detection and ranging (LiDAR) is becoming more common as an option in vehicles, which can detect rich geometric information in the environment for ego-motion estimation. Aiming at taking advantage of the complementary characteristics of these onboard technologies to navigate in urban environments, a tightly coupled multi-GNSS precise point positioning (PPP)/INS/LiDAR integrated system is proposed. We also develop an LiDAR sliding-window plane-feature tracking method to further improve navigation accuracy and computational efficiency. The performance of the proposed integrated system was evaluated in vehicular experiments with different GNSS observation conditions. Results indicate that our proposed GNSS/INS/LiDAR integration can maintain submeter level horizontal positioning accuracy in GNSS-challenging environments, with improvements of (73.3%, 59.7%, and 64.2%) compared to traditional GNSS/INS integration. Moreover, the plane-feature tracking method is proved to outperform traditional point-to-line and point-to-plane scan matching in terms of accuracy and efficiency.

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