A Fast Particle Filter for Tracking an Uncooperative GNSS Interference Source

Global navigation satellite system (GNSS) services are vulnerable to intentional or unintentional radio frequency interference (RFI). GNSS interference sources can disrupt critical services that are dependent on GNSS and hence it is imperative to locate and disable these RFI sources. A particle filter-based method to track moving GNSS interference sources with unknown acceleration is proposed. The motion of the moving interference source is modelled using the kinematic equation with unknown acceleration input. The position of the RFI source is tracked by estimating the unknown acceleration from the observation and then using the estimated acceleration within the Particle Filter framework. In addition, the extrapolated single propagation technique (ESPT) is used to significantly reduce the processing time of the proposed particle filter. The performance is evaluated using angle of arrival (AOA) and time difference of arrival (TDOA) measurements from a field trial. The results show that the proposed approach improves the geo-localization precision significantly compared to the snap-shot least squares estimation-based approach. Further, the use of ESPT reduced the processing time by around <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$66.6\%$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$29.9\%$</tex-math></inline-formula> for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$4^{th}$</tex-math></inline-formula>-order Runge-Kutta and Euler integration techniques, respectively, without impacting the performance.