UniMSF: A Unified Multi-Sensor Fusion Framework for Intelligent Transportation System Global Localization
Abstract
Intelligent transportation systems (ITS) localization is of significant importance as it provides fundamental position and orientation for autonomous operations like intelligent vehicles. Integrating diverse and complementary sensors such as global navigation satellite system (GNSS) and 4D-radar can provide scalable and reliable global localization. Nevertheless, multi-sensor fusion encounters challenges including heterogeneity and time-varying uncertainty in measurements. Consequently, developing a reliable and unified multi-sensor framework remains challenging. In this paper, we introduce UniMSF, a comprehensive multi-sensor fusion localization framework for ITS, utilizing factor graphs. By integrating a multi-sensor fusion front-end, alongside outlier detection\&noise model estimation, and a factor graph optimization back-end, this framework accomplishes efficient fusion and ensures accurate localization for ITS. Specifically, in the multi-sensor fusion front-end module, we tackle the measurement heterogeneity among different modality sensors and establish effective measurement models. Reliable outlier detection and data-driven online noise estimation methods ensure that back-end optimization is immune to interference from outlier measurements. In addition, integrating multi-sensor observations via factor graph optimization offers the advantage of \enquote{plug and play}. Notably, our framework features high modularity and is seamlessly adapted to various sensor configurations. We demonstrate the effectiveness of the proposed framework through real vehicle tests by tightly integrating GNSS pseudorange and carrier phase information with IMU, and 4D-radar.
Authors 10
-
Affiliation as printed
School of Automotive Studies , Tongji University , Shang- hai 201804 , China
-
Affiliation as printed
School of Automotive Studies , Tongji University , Shang- hai 201804 , China
-
Affiliation as printed
School of Automotive Studies , Tongji University , Shang- hai 201804 , China
-
Affiliation as printed
School of Automotive Studies , Tongji University , Shang- hai 201804 , China
-
Affiliation as printed
Shanghai Gongji Technology Co., Ltd , Shanghai 201804 , China
-
Affiliation as printed
Institute for Automotive Engineering (ika) , RWTH Aachen University , Aachen , 52062 , Germany
-
Wuhan University · State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Affiliation as printed
State Key Laboratory of Surveying Mapping and Remote Sensing Wuhan University , Wuhan , China
-
Wuhan University of Technology
Affiliation as printed
Intelligent Transportation System Research Center , Wuhan University of Technology , Wuhan , China
-
Affiliation as printed
School of Automotive Studies , Tongji University , Shang- hai 201804 , China
Cited by 0 stored of 0
No patents citing this paper on Lens.org (checked 2026-10-06).