GNSS Cloud-Data Processing Technique for Jamming Detection and Localization

In this paper, assuming that a jammer is located in an area where a large number of low-cost GNSS receivers are densely distributed over and their received signals are gathered into a central processing unit like a cloud-data, we propose a 2-dimensional time-frequency correlation method for the cloud-data which can determine the type of jamming signal and estimate the jammer’s position. This method is applied for examining the similarity between arbitrary two signals acquired from different receivers, thereby discriminating the presence and the type of a jamming signal in the time-frequency domain and also estimating the jammer’s position. The availability of the proposed method is examined by a numerical simulation, where 15 GNSS receivers are randomly placed at the certain distances that range from 100 [m] to 300 [m] from the jammer, so that the jamming to signal ratio(J/S) at the receiver varies as distance increases. Finally, we analyze the results of the time-frequency correlation method to confirm that the jamming signal can be detected and the position of the jammer can be estimated.