The Autocovariance Least-Squares Technique for GPS Measurement Noise Estimation

Abstract

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.