Abstract
In this paper, the Autocovariance Least Squares (ALS) technique is proposed for detecting the Global Positioning System (GPS) measurements’ interference or jamming. The interference is modeled by a moderate increase in the measurements noise covariance matrix while jamming is modeled by a larger increase in the measurements noise covariance matrix. The method makes use of the dynamics of the system measured by an inertial measurement unit (IMU) and the propagated residual of an ultra-tightly coupled GPS/IMU Extended Kalman filter (EKF) to form a bank of statistics used to estimate the GPS measurement-noise covariance. Simulated scenarios of different levels of noise magnitude are applied and the proposed method is used to estimate the GPS pseudorange noise covariance matrix. Results are presented at the end of the paper to show the accuracy of the proposed algorithm. The algorithm presented in this paper is vital for high-integrity operation of autonomous navigation systems.
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