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INS/GNSS Integrated Navigation Systems
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INS/GNSS Integrated Navigation Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 432

Special Issue Editor

Dr. Xiyuan Chen

E-Mail Website
Guest Editor
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
Interests: navigation and positioning; integrated navigation; optical sensors; GPS; measurement
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advent of Integrated Navigation Systems, combining Inertial Navigation Systems (INS) with Global Navigation Satellite Systems (GNSS), marks a significant milestone in the evolution of navigation technology. This Special Issue of our journal delves into the synergistic integration of INS and GNSS and other sensors, aiming to highlight the latest advancements, methodologies, and applications in this domain. As these systems complement each other’s strengths and mitigate their respective weaknesses, their integration paves the way for superior accuracy, reliability, and robustness in navigation solutions.

In this Special Issue, we invite researchers to present their innovative work on algorithm development, system design, sensor fusion techniques, and performance analysis of INS/GNSS integrated systems. We are particularly interested in articles that explore the challenges of environmental factors on system performance, the incorporation of machine learning for adaptive filtering, and the deployment of these systems in autonomous vehicles, aerospace, and mobile mapping. Through comprehensive research articles, reviews, and case studies, this Special Issue aims to provide a platform for disseminating cutting-edge research that pushes the boundaries of navigation technology.

Dr. Xiyuan Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • inertial navigation systems
  • GNSS
  • sensor fusion
  • integrated navigation
  • Kalman filter

Published Papers (1 paper)

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Research

17 pages, 4444 KiB  
Article
A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints
by Haiyang Qiu, Yun Zhao, Hui Wang and Lei Wang
Sensors 2024, 24(13), 4419; https://doi.org/10.3390/s24134419 - 8 Jul 2024
Viewed by 7
Abstract
In GNSS/IMU integrated navigation systems, factors like satellite occlusion and non-line-of-sight can degrade satellite positioning accuracy, thereby impacting overall navigation system results. To tackle this challenge and leverage historical pseudorange information effectively, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. [...] Read more.
In GNSS/IMU integrated navigation systems, factors like satellite occlusion and non-line-of-sight can degrade satellite positioning accuracy, thereby impacting overall navigation system results. To tackle this challenge and leverage historical pseudorange information effectively, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. These virtual constraints in the graph model are derived from the satellite’s position from the previous time step, the rate of change of pseudoranges, and ephemeris data. This virtual constraint serves as an alternative solution for individual satellites in cases of signal anomalies, thereby ensuring the integrity and continuity of the graph optimization model. Additionally, this paper conducts an analysis of the graph optimization model based on these virtual constraints, comparing it with traditional graph models of GNSS/IMU and SLAM. The marginalization of the graph model involving virtual constraints is analyzed next. The experiment was conducted on a set of real-world data, and the results of the proposed method were compared with tightly coupled Kalman filtering and the original graph optimization method. In instantaneous performance testing, the method maintains an RMSE error within 5% compared with real pseudorange measurement, while in a continuous performance testing scenario with no available GNSS signal, the method shows approximately a 30% improvement in horizontal RMSE accuracy over the traditional graph optimization method during a 10-second period. This demonstrates the method’s potential for practical applications. Full article
(This article belongs to the Special Issue INS/GNSS Integrated Navigation Systems)
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