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Advances in GNSS/INS Integration for Navigation and Positioning

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

Deadline for manuscript submissions: 30 October 2026 | Viewed by 1228

Special Issue Editors


E-Mail Website
Guest Editor
School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China
Interests: cooperative positioning; MIMO communication; big data fusion; information fusion
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
2. Research & Development Institute, Northwestern Polytechnical University in Shenzhen, Shenzhen 518063, China
Interests: cooperative positioning; high-speed communication; big data fusion; array antennas
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China
Interests: low-orbit satellite communication and navigation integration; wireless communication and positioning; multi-source fusion navigation; wide-area aviation search and rescue

Special Issue Information

Dear Colleagues,

Global Navigation Satellite Systems (GNSS) have transitioned from niche applications to foundational infrastructure that is essential for the functioning of modern society. They enable precise navigation for autonomous vehicles and unmanned systems, ensure critical timing in communications, and support Earth observation through methods such as reflectometry. Nevertheless, achieving uninterrupted, high-integrity, centimeter-level positioning in challenging environments—such as urban canyons with severe signal blockage and multipath, under interference, or during high-dynamic maneuvers—remains an ongoing challenge that demands continuous innovation.

This Special Issue seeks to showcase state-of-the-art research advancing the integration of GNSS with Inertial Navigation Systems (INS) and other complementary sensors. We welcome submissions addressing key developments in the following areas: multi-constellation and multi-frequency GNSS processing, tightly coupled GNSS/INS and multi-sensor fusion (e.g., with LiDAR, cameras, or odometry), high-precision algorithms including PPP-RTK and fast ambiguity resolution, and resilient positioning techniques for GNSS-degraded or denied environments. Contributions focusing on low-cost, high-performance GNSS/INS architectures and the exploitation of emerging signals are also highly encouraged.

The insights gathered in this issue will serve as a valuable resource for researchers and engineers, promoting the development of robust, precise, and seamless navigation systems to support transformative applications in intelligent transportation, smart cities, precision agriculture, and beyond.

Dr. Yangyang Liu
Dr. Chengkai Tang
Dr. Zesheng Dan
Guest Editors

Manuscript Submission Information

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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

  • GNSS
  • INS
  • precise positioning
  • multi-sensor fusion
  • PPP-RTK
  • urban navigation
  • ambiguity resolution
  • integrity monitoring
  • autonomous systems
  • low-cost receivers
  • signal processing

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Published Papers (2 papers)

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Research

20 pages, 4400 KB  
Article
Tightly Coupled GNSS/IMU Hybrid Navigation Using Factor Graph Optimization with NLOS Detection Capability
by Haruki Tanimura and Toshiaki Tsujii
Sensors 2026, 26(7), 2264; https://doi.org/10.3390/s26072264 - 6 Apr 2026
Viewed by 565
Abstract
High-precision and reliable self-localization is essential for autonomous navigation systems. However, in urban canyons (urban environments with clusters of high-rise buildings), Global Navigation Satellite Systems (GNSS) suffer from severe multipath and Non-Line-of-Sight (NLOS) signal reception. This causes a theoretically unbounded positive bias in [...] Read more.
High-precision and reliable self-localization is essential for autonomous navigation systems. However, in urban canyons (urban environments with clusters of high-rise buildings), Global Navigation Satellite Systems (GNSS) suffer from severe multipath and Non-Line-of-Sight (NLOS) signal reception. This causes a theoretically unbounded positive bias in pseudorange measurements, significantly degrading positioning integrity. To address this challenge, this study proposes a novel GNSS/Inertial Measurement Unit (IMU) tightly coupled integrated navigation system using factor graph optimization (FGO) integrated with machine learning-based NLOS detection. To train the NLOS detection model, we utilized a dual-polarized antenna to label signals based on the strength difference between RHCP and LHCP components, achieving a detection accuracy of 0.89. A random forest classifier identifies NLOS signals, and based on its classification labels, the variance of the corresponding GNSS pseudorange factors within the FGO framework is dynamically inflated. This effectively mitigates the impact of outliers while preserving the graph topology. Experimental evaluations in dense urban environments demonstrated that the proposed method improves horizontal positioning accuracy by 84.8% compared to conventional standalone GNSS positioning. The dynamic integration of machine learning-based signal classification and tightly coupled FGO provides an extremely robust positioning solution, proven to meet the stringent reliability requirements demanded of autonomous systems even under severe signal obscuration. Full article
(This article belongs to the Special Issue Advances in GNSS/INS Integration for Navigation and Positioning)
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32 pages, 5650 KB  
Article
High-Accuracy Wave Direction Estimation Using Kalman Fusion of Interferometric Measurements and Energy Field Reconstruction
by Caicheng Wang, Xue Li and Linshan Xue
Sensors 2026, 26(6), 1852; https://doi.org/10.3390/s26061852 - 15 Mar 2026
Viewed by 314
Abstract
Microwave wireless power transfer (MWPT) for space solar power stations (SSPS) requires high-precision beam pointing in order to maintain effective aperture coupling and transmission efficiency under platform motion and disturbances. This paper proposes a dual-link beam pointing estimation framework that integrates guidance-link interferometric [...] Read more.
Microwave wireless power transfer (MWPT) for space solar power stations (SSPS) requires high-precision beam pointing in order to maintain effective aperture coupling and transmission efficiency under platform motion and disturbances. This paper proposes a dual-link beam pointing estimation framework that integrates guidance-link interferometric angle-of-arrival (AoA) measurements with power-link energy-field reconstruction. The interferometric chain provides high-rate azimuth and elevation observations for dynamic tracking, while the energy-field reconstruction estimates the energy-centroid displacement from the received-aperture power distribution to correct steady-state pointing bias. A Kalman filter (KF) is developed to fuse the asynchronous multi-rate measurements, yielding continuous and robust pointing estimates for closed-loop beam control. Simulation results show that the proposed fusion method achieves azimuth and elevation RMSEs of 0.0069° and 0.006° with interferometric and energy-centroid error levels of approximately 0.05° and 0.02°, respectively, significantly reducing high-frequency fluctuations. In addition, a sensitivity model is established to quantify the impact of angular errors on capture efficiency. The expected efficiency improves from approximately 0.988 and 0.998 for the individual methods to nearly unity for the fusion output. Quantitative accuracy thresholds corresponding to different efficiency requirements are further derived, providing practical guidelines for SSPS MWPT system design. Full article
(This article belongs to the Special Issue Advances in GNSS/INS Integration for Navigation and Positioning)
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