Complex delay and frequency of GNSS signal tracking algorithm based on optimal trajectory filtering technique

GNSS user-end equipment performance depends highly on signal tracking systems quality. Usually these tracking systems are based on well-known extended Kalman filter approach. This approach uses Gaussian aposteriori probability function approximation. This approximation is not accurate in poor signal environment. This results in inaccurate signal parameters estimation and even tracking loss. One of possible approaches to improve this is optimal trajectory filtering. In the article complex delay and frequency tracing is implemented with this technique. It is shown that this technique provides more accurate estimations in low signal to noise ratio compared to extended Kalman filter.