Document Type

Article

Date of Original Version

2018

Abstract

GNSS are well known to be accurate providers of position information across the globe. Because of high signal availabilities, robust receivers, and well-populated constellations, operators typically believe that the location information provided by their GNSS receiver is correct. More sophisticated users are concerned with the integrity of the derived location information; for example, employ RAIM algorithms to address possible satellite failure modes. The most common attacks on GNSS availability and integrity are known as jamming and spoofing. Jamming involves the transmission of signals that interfere with GNSS reception so that the receiver is unable to provide a position or time solution. Various methods to detect jamming, and possibly overcome it, have been considered in the literature. Spoofing is the transmission of counterfeit GNSS signals so as to mislead a GNSS receiver into reporting an inaccurate position or time. If undetected, spoofing might be much more dangerous than a jamming attack. A typical maritime concern is a spoofer convincing a tanker traveling up a channel to a harbor that it is off track of the channel. A variety of approaches have been proposed in the literature to recognize spoofing; many of these are based on the RF signal alone as, in some sense, they are the simplest to implement. Of interest here are methods which compare GNSS information to measurements available from other, non-GNSS sensors. Examined examples include IMUs, radars, and ranges/pseudoranges from non-GNSS signals. In all cases the data from these others sensors is compared to the position information from the GNSS receiver to assess its integrity. Triangulation of position from bearing measurements is a well-known localization technique, especially for the mariner. This paper considers the use of bearing information to detect GNSS spoofing in a 2-D environment. A typical marine application is a ship entering a harbor and using an alidade to sight landmarks; for mobile, autonomous vehicles the sensor might be a camera taking a bearing to a nearby vehicle or to a signpost. This paper presents a mathematical formulation of the problem and the sensor data, develops a statistical model of the measurements relative to the GNSS position output, constructs a generalized likelihood ratio test detection algorithm based on the Neyman-Pearson performance criterion (maximizing probability of detection while bounding the probability of false alarm), and examines performance of the test, both through analysis and experimentation. A comparison to using both range and bearing is included to show the utility and limitations of bearing data to spoof detection.

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