A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions
This paper presents a new approach to estimate the true position of an unmanned aerial vehicle (UAV) in the conditions of spoofing attacks on global positioning system (GPS) receivers. This approach consists of two phases, the spoofing detection phase which is accomplished by hypothesis test and the trajectory estimation phase which is carried out by applying the adapted particle filters to the integrated inertial navigation system (INS) and GPS. Due to nonlinearity and unfavorable impacts of spoofing signals on GPS receivers, deviation in position calculation is modeled as a cumulative uniform error. This paper also presents a procedure of applying adapted particle swarm optimization filter (PSOF) to the INS/GPS integration system as an estimator to compensate spoofing attacks. Due to memory based nature of PSOF and benefits of each particle’s experiences, application of PSOF algorithm in the INS/GPS integration system leads to more precise positioning compared with general particle filter (PF) and adaptive unscented particle filer (AUPF) in the GPS spoofing attack scenarios. Simulation results show that the adapted PSOF algorithm is more reliable and accurate in estimating the true position of UAV in the condition of spoofing attacks. The validation of the proposed method is done by root mean square error (RMSE) test.
KeywordsInertial navigation system (INS)/global positioning system (GPS) integration unmanned aerial vehicles (UAVs) position estimation spoofing particle based filters
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The authors would like to acknowledge Dr. Saeed Nasrollahi from the Sharif University of Technology in Tehran for providing constructive feedback, careful reading and compassionate guidance to improve the article, Ehya Yavari from the Institute of Robotics and Computer (IRC) in Malek-Ashtar University of Technology in the field of LORAN-C national project, for his supporting behavior and Dr. Mahdi Majidi, the faculty member of University of Kashan because of his careful advices to improve this article.
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