GNSS Data Processing and Navigation in Challenging Environments

Dear Colleague:

Global navigation satellite systems (GNSS) are the core technology for many kinds of applications in terms of positioning and navigation. With the advent of low-cost multi-GNSS and multi-frequency receivers, the use of GNSS will become more popular—especially in precise positioning such as DGNSS, RTK, and PPP. However, GNSS also has  unstable accuracy in challenging environments and is very vulnerable to interference. To cope with these issues, many researchers are currently developing and improving signal processing, data processing, multi-GNSS/frequency capability use, and sensor or feature aiding. It is very important for us to improve the accuracy, availability, and reliability of GNSS for future critical applications such as autonomous driving, unmanned monitoring of construction, and surveys in difficult environments as well as unmanned aerial and ground vehicles.

The aim of this Special Issue is to collect high-quality research articles and review papers on advances in GNSS data processing and navigation in challenging environments. Developments that improve the performance and efficiency of GNSS data processing for typical urban conditions (strong multipath, NLOS, etc.), machine learning and neural network approaches to GNSS, and sensor fusion using IMU, speed, camera and Lidar etc. 3D map aiding are also welcome.

Dr. Nobuaki Kubo
Dr. Taro Suzuki
Dr. Yize Zhang
Guest Editors

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