An Interference Localization Algorithm Based on Gaussian Approximation Particle Filtering with Stable Distribution Noise

The ground-air communication of civil aviation is interfered by radios, which has seriously endangered the normal flight of civil airplanes. This paper proposes a Gaussian approximation particle filtering (GAPF) algorithm based on study of the method of interference localization that utilizes Doppler frequency shifts of the scattered signals from airplanes. The main contribution of this paper can be summarized as follows. First, study on the nonlinear relationship between Doppler frequency shifts and the coordinates of the interference, and construct the state-space equation and the measurement equation. Second, use the additive symmetric alpha stable (SaS) distribution noise to describe the scattered channel model, and propose the Gaussian approximation particle filtering algorithm under the assumption of SaS noise. Numerical simulations demonstrate that the proposed algorithm can achieve better estimation performance and robustness for additive noise, compared with the extended Kalman filter (EKF) and the unscented Kalman filter (UKF).