A GNSS Interference Source Tracking Method Using the Continuous-Discrete Gaussian Kernel Quadrature Kalman Filter

Global Navigation Satellite Systems (GNSSs) are vulnerable to interference due to low satellite signal transmission power, and thus the problem of tracking GNSS interference sources has attracted much attention. A new nonlinear filtering algorithm called the continuous-discrete Gaussian kernel quadrature Kalman filter (CD-GKQKF) is proposed for tracking such interference sources. Continuous-discrete filtering framework considers the process model as being in the continuous-time domain and subsequently constructs the univariate Gaussian kernel quadrature (GKQ) rule based on scaled Gaussian Hermite quadrature rule. On that basis, it is extended to the multivariate space with tensor product rule. Finally, the multivariate GKQ rule is introduced into the continuous-discrete filtering framework and the CD-GKQKF algorithm is obtained. The proposed algorithm has been applied to the Van der Pol Oscillator and the GNSS interference source tracking application, respectively. The results show that the proposed CD-GKQKF algorithm with appropriate Gaussian kernel bandwidth provides better accuracy than the traditional continuous-discrete filtering algorithms.