Topic Editors

Prof. Dr. Hang Guo
School of Information Engineering, Nanchang University, Nanchang, China
Dr. Marcin Uradzinski
Faculty of Geoengineering, University of Warmia and Mazury, 10-720 Olsztyn, Poland
Prof. Dr. You Li
Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Multi-Sensor Integrated Navigation Systems

Abstract submission deadline
31 March 2023
Manuscript submission deadline
30 June 2023
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Topic Information

Dear Colleagues, 

Multi-sensor integrated navigation systems have become a hot area of research and have made significant progress in both theoretical investigation and practical applications. Various intelligent and advanced multi-sensor fusion and data analysis algorithms and technologies have been applied in many fields, such as sensor networks, automation, monitoring, micro/nano systems, operation, control, field robotics, navigation and autonomous vehicles. In all these applications, the key enabling technologies focus on localization and navigation. 

Many recent studies have been focused on the integration of GNSS systems with a variety of underlying sensor technologies, such as MEMS IMU, RF (Radio Frequency), cameras, ultrasonic sensors, laser scanners, magnetometers, and barometers. The fusion scheme can use all data from these sensors and overcome their limitations, which provides a reliable and precise navigation. The multi-dimensional capabilities of the recent mobile computing of inexpensive devices (including smartphones, tablets, and wearables) has shown the way for new personalized services, such as indoor localization, which nowadays represents a major scientific and technological challenge. 

Multi-sensor integrated navigation systms have become key to add location and motion context to data in various areas, from robots and self-driving cars to smartphones and internet-of-things (IoT) devices. In recent years, technological advancements have facilitated the manufacturing of compact, inexpensive, and low-power navigation and sensing (e.g., inertial navigation, computer vision, LiDAR, wireless, magnetic, light, and sound) sensors for smart devices. These advances have led to the fast development of navigation sensors, data processing, and related services. Multi-sensor integrated navigation is a mainstream direction to design an accurate, low-cost, low-power, reliable, and scalable navigation system for cutting-edge applications. Extensive research efforts have been paid to multi-sensor integrated navigation algorithms, architectures, and systems. 

This Topic is devoted to new advances and research results on multi-sensor fusion and data analysis to attract widespread attention to the many research fields that apply various positioning methods in indoor and outdoor environments. The applications of various multi-sensor fusion technologies and of various systems are also welcome. This Topic will also consider articles introducing novel ideas and algorithms and the latest advances in the field of multi-sensor data fusion coupled with any prototype implementations and evaluations. 

This Topic include, but are not limited to: 

GNSS and RF Theory, New Technologies and Algorithms

  • GNSS/IMU conbimed system for Aeronautical and Astronautical Engineering;
  • GNSS theories and applications for Sea and Ocean;
  • GNSS Continuously Operating Reference Stations (CORS);
  • New GNSS  Ionospheric and Tropospheric technologies and algorithms;
  • GNSS Metereology;
  • New GNSS technologies for monitering wind power generation system, wild life, etc.;
  • High precision mobile phone positioning based on GNSS, IMU, and other sensors;
  • WiFi, IMU, LiDAR, and camera sensors for pedestrian navigation;
  • Bluetooth Angle of Arrival (AOA) for positioning and navigation;
  • UWB-based locating systems;
  • GNSS, IMU, and camera sensors for live entertainment, 3D tourism devices, etc.;
  • GNSS for Transportation, Agriculture, Forestry, Fishery, Mining and other projects;
  • Precise Point Positioning (PPP): new technologies and algorithms. 

Multi-sensor Fusion System

  • Multi-sensor fusion for precise navigation;
  • Sensor signal processing and data analysis;
  • Applications of machine learning;
  • Optimal sensor placement;
  • Multi-sensor fusion for 3D localization;
  • Intelligent multi-sensor fusion for indoor navigation;
  • Multi-sensor-based monitoring and operation, and simultaneous localization and mapping (SLAM);
  • Multi-sensor-based control system for machine, vehicles, etc.;
  • Localization and Internet of Things;
  • Modelling and analysis of multi-sensors;
  • Software and hardware development for multi-sensor fusion;
  • Algorithms to combine sensors for pedestrian navigation or localization;
  • Automatic indoor mapping for navigation and tracking systems and smartphone multi-sensor fusion. 

Wearable Navigation and Unmanned Navigation

  • New wearable navigation and sensing sensors and applications;
  • Algorithms and systems for smart wearable positioning;
  • Data-driven wearable navigation;
  • Interaction between smart wearables and robots;
  • Combination of wearable navigation and autonomous driving;
  • Application of smart wearable motion sensing in medical health;
  • The use of smart wearable navigation in public safety;
  • Smart wearable AR and VR;
  • Geoinformation systems on data from wearable devices;
  • Unmanned Aerial Vehicle (UAV) with multi-sensors.

Prof. Dr. Hang Guo
Dr. Marcin Uradzinski
Prof. Dr. You Li
Topic Editors


  • GNSS
  • Continuously Operating Reference Stations (CORS)
  • Precise Point Positioning
  • GNSS/MEMS IMU integration
  • internet-of-things
  • WiFi localization
  • bluetooth angle of arrival
  • SLAM
  • LiDAR
  • indoor positioning
  • unmanned aerial vehicle
  • applications of multi-sensor fusion
  • mobile phone positioning
  • wearable positioning
  • unmanned navigation

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
1.659 3.0 2014 22.8 Days 1600 CHF Submit
Applied Sciences
2.679 3.0 2011 17.7 Days 2300 CHF Submit
Remote Sensing
4.848 6.6 2009 19.8 Days 2500 CHF Submit
3.576 5.8 2001 17.4 Days 2400 CHF Submit
Smart Cities
- - 2018 20.6 Days 1200 CHF Submit

Published Papers (1 paper)

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Inversion Method of Tidal Level Based on GNSS Triple-Frequency, Geometry-Free, Non-Ionospheric Phase Combination
Appl. Sci. 2022, 12(10), 4983; - 14 May 2022
Using the navigation signal transmitted by GNSS (global navigation satellite system), satellites for tide level monitoring comprise one of the important research fields of GNSS marine remote sensing. Regarding the problem that GNSS-MR (multipath reflectometry) technology only uses carrier SNR (signal noise ratio) [...] Read more.
Using the navigation signal transmitted by GNSS (global navigation satellite system), satellites for tide level monitoring comprise one of the important research fields of GNSS marine remote sensing. Regarding the problem that GNSS-MR (multipath reflectometry) technology only uses carrier SNR (signal noise ratio) data, resulting in the lack of SNR data for early CORS (continuously operating reference stations) stations, it is impossible to carry out tide level inversion. In this paper, a method of tide level inversion based on triple-frequency geometric ionospheric free combined-phase observations instead of SNR is proposed. The simultaneous interpretation of GNSS satellite observations from the sc02 station in Friday Harbor in the US is carried out and compared with the traditional GNSS-IR (interference and reflectometry) tide-inversion method. The experimental results show that the tide level inversion method proposed in this paper has the same tide level trend as the measured tide level trend. The accuracy evaluation shows that the RMSE value of tide level inversion is 15 cm and the correlation coefficient r is 0.984, which verifies the effectiveness of this method for tide level monitoring and expands the method of GNSS tide-level monitoring. Full article
(This article belongs to the Topic Multi-Sensor Integrated Navigation Systems)
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