GNSS cloud-data processing technique for jamming detection, identification, and localisation

Low-cost signal jammers, which are illegal in many countries but continue to be traded in the black market, emit weak global navigation satellite system (GNSS) jamming signals. This study proposes a method to detect, identify, and localise these signals based on a cloud-data processing technique in which the jamming detection, identification, and localisation are performed sequentially after gathering received signals from low-cost GNSS receivers distributed in a monitoring network. This technique consists of two steps: two-dimensional image correlation in the time-frequency domain for detection and identification, and signal correlation in the time domain and relevant processing for localisation. For this, technical descriptions of the proposed cloud-data processing method are first presented with various jamming scenarios. Then, numerical simulations are performed to evaluate the proposed method by generating satellite and jamming signals. The authors are thus able to verify the feasibility of the technique and conclude that, in practical applications, it would allow efficient and extensive monitoring of low-cost signal jammers.