Improved characterization of GNSS jammers using short-term time-frequency rényi entropy

Availability of global navigation satellite system (GNSS) jammers sold as personal privacy devices poses a severe threat to civilian systems that rely on GNSS signals to function. Typically, the large sweep bandwidth of these jammers within a short sweep time makes it difficult to characterize accurately their instantaneous frequency (IF) functions with a view to excising them from the received signal. This results in degraded jammer excision. In this paper, an improved jammer characterization algorithm using time-frequency (TF) analysis is proposed. For the most common chirp-type jammer with one or multi saw-tooth function, short-term Rényi entropy is used to provide information about the turning points in the IF function, which are then used to generate the improved jammer signal IF estimates. Simulation results show that the proposed algorithm alleviates the dominant impulsive-nature IF estimation errors for strong jammers, and thus improves the performance of the IF estimation-based jammer mitigation techniques.