Vector Tracking Algorithm Based on Adaptive Cubature Kalman Filter

Abstract

In the vector tracking loop, there is a great error in the output of discriminator owing to the disturbance of noise. Cubature Kalman filter is proposed to replace the discriminator to process I/Q data and generate code phase error and the carrier frequency error in this paper. The present algorithm not only can avoid the nonlinear problem of discriminator, but also can reduce the bad effect of noise. Moreover, using cubature Kalman filter to deal with the nonlinear I/Q data is beneficial to preserve the accuracy of data processing. Because noise is unknown or time-varying, the filter should have the ability to respond to the changes of environmental noise. The innovation of measurements is used to estimate the covariance matrix of measurement noise in real time. Finally, a comparison is carried out between the present algorithm and the vector tracking algorithm based on discriminator. The test results show that the code phase error and the carrier frequency error are smaller, and the accuracy of navigation solution is also higher.

Keywords

• gnss
• vector tracking loop
• cubature kalman filter
• innovation