The Autocovariance Least-Squares Technique for GPS Measurement Noise Estimation

In this paper, the autocovariance least-squares (ALS) technique is proposed to estimate the Global Positioning System (GPS) pseudorange measurement noise-covariance matrix. The large GPS measurement noise magnitude can be attributed to signal interference, jamming, or other factors, such as signal multipath. The proposed method makes use of the dynamics of the system measured by an inertial measurement unit (IMU) and the propagated residual of a GPS/IMU estimation filter to form a bank of statistics used to estimate the GPS measurement noise covariance. The method is used along an ultratightly coupled GPS/IMU filter to first estimate the measurement noise covariance matrix and then use this covariance matrix to obtain a high-accuracy and high-integrity state estimate. Simulated scenarios of different levels of noise magnitude are applied, and the proposed method is used to estimate the GPS pseudorange noise-covariance matrix.