GNSS Spoofing Detection by Means of Signal Quality Monitoring (SQM) Metric Combinations
Author(s) -
Chao Sun,
Joon Wayn Cheong,
Andrew G. Dempster,
Hongbo Zhao,
Wenquan Feng
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2875948
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Global navigation satellite system (GNSS) signal is vulnerable and easily interfered by spoofing because of its opening signal structure and weak signal power. A signal quality monitoring (SQM) technique has been shown to be viable to detect spoofing attacks on GNSS signals. However, the effectiveness of spoofing detection employing a single SQM metric alone is limited and conditional upon the features extracted of that specific SQM metric. The complementary features among various SQM metrics can be exploited to implement joint detection to overcome the deficiency of the individual SQM metric. Motivated by this idea, this paper investigates the multi-metric joint detection technique, which combines various SQM metrics into a composite SQM metric to detect spoofing attacks. This paper proposes two combination strategies, namely amplitude combination mode and probability of false alarm combination mode (PfaM). The overall performance of different metric combinations was verified using simulations and the Texas Spoofing Test Battery dataset. Results show that the PfaM detector outperforms all single SQM metric detectors under various scenarios.
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