A maneuvering multi-sensor information fusion algorithm for enhancing localization reliability in ADAS testing

IF 2.9 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Digital Signal Processing Pub Date : 2025-01-13 DOI:10.1016/j.dsp.2025.104991

Liyang Sun , Lin Xu , Xue Dong , Muhammad Usman Shoukat , Jia Mi

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引用次数: 0

Abstract

A novel algorithm, the maneuvering first-order generalized pseudo-Bayesian error-state Kalman filter (MGPB1-ESKF), is proposed in this study for localization in advanced driver assistance system (ADAS) testing platform vehicles. The proposed algorithm substantially enhances the reliability and accuracy of multi-sensor localization in ADAS testing. This improvement is particularly significant in challenging non-line-of-sight (NLOS) environments, which typically degrade the performance of global navigation satellite system (GNSS). By adaptively identifying and isolating faulty signal sources, the MGPB1-ESKF provides a novel approach to achieving robust and reliable localization in the presence of transient sensor failures. Rigorous simulations and experimental results demonstrate that the proposed algorithm effectively mitigates the impact of faulty sensors in challenging environments, outperforming conventional multiple model (MM) algorithm and leading to improved localization accuracy.

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来源期刊

Digital Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

17.20%

发文量

435

审稿时长

66 days

期刊介绍： Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,