@inproceedings{fdf1cab6257c454d8310d6214c3de553,
title = "Particle Filter based approach for GNSS interference source tracking: a feasibility study",
abstract = "Global Navigation Satellite System (GNSS) signals are vulnerable to intentional or unintentional Radio Frequency Interference (RFI) sources. Since GNSS is used in numerous critical services, it is of interest to accurately localise and track the RFI source to take further actions. This paper explores the possibility of implementing the Particle Filter for localising a moving GNSS RFI source using Angle of Arrival (AOA) and Time Difference of Arrival (TDOA) observations. The performance of the Particle Filter and the Single Propagation Unscented Kalman Filter (SPUKF) are compared in this context in terms of estimation accuracy, the standard deviation in error and the processing time.",
author = "Biswas, \{Sanat K.\} and Ediz Cetin",
year = "2020",
doi = "10.23919/URSIGASS49373.2020.9232443",
language = "English",
isbn = "9781728156903",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "1--4",
booktitle = "2020 XXXIIIrd General Assembly and Scientific Symposium of the International Union of Radio Science",
address = "United States",
note = "33rd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2020 ; Conference date: 29-08-2020 Through 05-09-2020",
}