Data Fusion Methods and AI Technologies for Resilient PNT in Challenging Observation Areas

Dear Colleagues,

The provision of continuous and high-precision positioning information is crucial for activities such as route planning, vehicle navigation, and autonomous driving, especially in challenging observation environments such as city canyons and underground or partially obstructed areas. In recent years, significant progress has been made in the following aspects:

• The development of multi-constellation global navigation satellite systems (GNSS) and their ground- and satellite-based augmentation infrastructure, along with advancements in 5G/LEO communication technologies.
• The steady increase in the manufacturing level of sensors such as laser scanners, IMUs, vision systems, mm-wave radars, etc.
• Embedded systems for positioning and navigation have become increasingly powerful in their hardware configurations, which enables faster program speed, more run-time storage, and better concurrent computation ability.
• Advances in nonlinear optimization theory, such as bundle adjustment and factor graph theories which support sensors to work in a plug-and-play manner, combined with the latest artificial intelligence technologies, especially deep learning, provide a better and more robust non-linear optimization framework for fusing multi-sensor data in real-time.

The aforementioned progress offers enormous potential and possibilities to obtain increasingly robust and precise positioning ability and deliver resilient PNT services in challenging areas.

This Special Issue of Remote Sensing aims to provide a platform for researchers to publish innovative work that pushes the boundaries of real-time GNSS utilization and enhances the opportunity to provide increasingly precise and robust positioning ability through multi-sensor data fusion and support with the latest AI technologies, even when GNSS services are totally blocked. For instance, technologies that enable the quick capture of GNSS services and provide reliable positioning ability in semi-obscured environments, support high-precision absolute positioning information injection in long-term GNSS-denied areas, and provide continuous positioning ability through the fusion of IMU/vision/map technology are welcome for publication in this Special Issue. Potential topics include, but are not limited to, the following:

• Fast capture and evaluation of GNSS service quality in semi-obscured environments;
• Integrated GNSS/5G positioning and navigation approaches;
• The application of high-resolution map in positioning, for example map-matching;
• Scene matching algorithm;
• Approaches for a priori and real-time map construction;
• Vision positioning technologies such as SLAM;
• Integrated Kalman and AI applications in resilient PNT;
• Advanced algorithms for integrated GNSS/IMU/LiDAR/Vision multi-sensor positioning and navigation;
• Real-time corrections of accumulated error and sensor parameter calibration.

Prof. Dr. Xiaoguo Zhang
Prof. Dr. Xiaolin Meng
Dr. Craig M. Hancock
Dr. Yuan Yang
Dr. Yujia Zhang
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 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.

• continuous positioning
• GNSS
• SLAM
• tight integration
• Kalman filter
• factor graph
• artificial intelligence
• non-linear optimization
• map aided positioning
• multi-sensor integration
• machine learning

• Integrated Applications of Real-Time GNSS Precise Positioning Services in Remote Sensing (24 articles)