Open AccessBook
GNSS -- global navigation satellite systems : GPS, GLONASS, Galileo, and more
Reads0
Chats0
TLDR
The next generation of positioning models for positioning and data processing will depend on the design of the satellite itself, as well as on the satellite orbits it is placed in.Citations
More filters
Book ChapterDOI
The Urgency and Principals of the Industry Policy Optimization for Beidou Satellite Navigation System
Junlin Yang,Xiangming Hu +1 more
TL;DR: In this paper, the development of satellite navigation system needs effective industrial policy guidance urgently to adapt the disorder even vicious competition in the beginning, and the government must adjust the market access mechanism to achieve the optimal resources allocation and strongest competitiveness.
Reference data and procedures for ground atmospheric radiometry for European Space Agency stations and campaigns
Saverio T. Nilo,Domenico Cimini,Sabrina Gentile,Salvatore Larosa,Antonio Martellucci,Mircea Fetescu,J. Villalvilla,Filomena Romano +7 more
TL;DR: Reference data and procedures for ground atmospheric radiometry for European Space Agency stations and campaigns activities are designed and presented in this article , where the authors aim to create a database of reference long-term simulations of atmospheric brightness temperature for monitoring radiometric accuracy and calibration and for developing retrieval algorithms to be used in the operations of ground-based microwave radiometers for atmospheric characterization.
Book ChapterDOI
Electromagnetic Characterization of Installed Antennas Through UAVs
TL;DR: The radiation pattern of a log-periodic antenna at 250 MHz has been measured with good results and some best practices in the use of such system for this particular field of application are defined to reach the expected result.
Journal ArticleDOI
Comparative analysis of blind tropospheric correction models in Ghana
LoRaWAN-implemented Node Localisation in a Sandstorm Environment based on Received Signal Strength Indicator
Ibrahim Aqeel,Ephraim Iorkyase,Hussein Mohammed Zangoti,Christos Tachtatzis,Robert Atkinson,Ivan Aondonovic +5 more
TL;DR: This paper presents an evaluation of the performance of LoRaWAN Received Signal Strength Indicator (RSSI)-based node localisation in a sandstorm environment and employs machine learning algorithms - Support Vector Regression and Gaussian Process Regression - which turns the high variance of RSSI to advantage; creating unique signatures representing different locations.