Using Mobile Phones for Participatory Detection and Localization of a GNSS Jammer

It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowds ensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio ($C / N_{0}$) estimates or automatic gain control (AGC) values. In this work, we exploit $C / N_{0}$ measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using $C / N_{0}$ measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.

I. Introduction

Global Navigation Satellite System (GNSS) receivers are widely spread in society, including society-critical services, today. It is also known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. Therefore, it is important to detect and localize the source of such attack, which can be hard without a dedicated sensing infrastructure. The notion of participatory sensing, or crowd-sensing, is that a large ensemble of voluntary contributors provides the measurements, rather than relying on a dedicated sensing infrastructure.