1 research outputs found
Signal processing techniques for GNSS anti-spoofing algorithms
The Global Navigation Satellite Systems (GNSS) usage is growing at a very high
rate, and more applications are relying on GNSS for correct functioning. With the
introduction of new GNSSs, like the European Galileo and the Chinese Beidou, in
addition to the existing ones, the United States Global Positioning System (GPS)
and the Russian GLONASS, the applications, accuracy of the position and usage of
the signals are increasing by the day.
Given that GNSS signals are received with very low power, they are prone to
interference events that may reduce the usage or decrease the accuracy. From these
interference, the spoofing attack is the one that has drawn major concerns in the
GNSS community. A spoofing attack consist on the transmission of GNSS-like
signals, with the goal of taking control of the receiver and make it compute an
erroneous position and time solution.
In the thesis, we focus on the design and validation of different signal processing
techniques, that aim at detection and mitigation of the spoofing attack effects. These
are standalone techniques, working at the receiver’s level and providing discrimination
of spoofing events without the need of external hardware or communication
links. Four different techniques are explored, each of them with its unique sets of
advantages and disadvantages, and a unique approach to spoofing detection. For
these techniques, a spoofing detection algorithm is designed and implemented, and
its capabilities are validated by means of a set of datasets containing spoofing signals.
The thesis focuses on two different aspects of the techniques, divided as per detection
and mitigation capabilities. Both detection techniques are complementary, their joint
use is explored and experimental results are shown that demonstrate the advantages.
In addition, each mitigation technique is analyzed separately as they require
specialized receiver architecture in order to achieve spoofing detection and mitigation.
These techniques are able to decrease the effects of the spoofing attacks, to the point
of removing the spoofing signal from the receiver and compute navigation solutions
that are not controlled by the spoofer and lead in more accurate end results.
The main contributions of this thesis are: the description of a multidimensional
ratio metric test for distinction between spoofing and multipath effects; the introduction
of a cross-check between automatic gain control measurements and the
carrier to noise density ratio, for distinction between spoofing attacks and other
interference events; the description of a novel signal processing method for detection
and mitigation of spoofing effects, based on the use of linear regression algorithms;
and the description of a spoofing detection algorithm based on a feedback tracking
architecture