摘要
Dual-frequency satellite positioning receivers are widely used because they can eliminate ionospheric delay and solve the full-circumference ambiguity quickly.However,in traditional dual-frequency receivers,the relevance of dual-frequency signals are not considered,and,with no improvement imposed to the tracking loop,two independent tracking loops are used to achieve the tracking of dual-frequency signals.In this paper,the Bei Dou dual-frequency signals joint tracking algorithm based on Kalman filter is proposed for the tracking of Bei Dou B1I and B3I dual-frequency signals.Taking the relevance of B1I and B3I signals into consideration,the algorithm adds a Kalman filter between the phase detector and carrier loop filter of the traditional dual-frequency independent tracking loop.The output results of the phase detectors of the B1I and B3I branches are then combined and filtered by the Kalman filter,and the results are input to the carrier loop filters of the corresponding branches.Proved by experiments,the algorithm not only enables the loop to enter a stable tracking state quickly,but also reduces the noise bandwidth of the two loop filters by about 10 Hz with the same tracking performance obtained.
Dual-frequency satellite positioning receivers are widely used because they can eliminate ionospheric delay and solve the full-circumference ambiguity quickly. However,in traditional dual-frequency receivers,the relevance of dual-frequency signals are not considered,and,with no improvement imposed to the tracking loop,two independent tracking loops are used to achieve the tracking of dual-frequency signals. In this paper,the Bei Dou dual-frequency signals joint tracking algorithm based on Kalman filter is proposed for the tracking of Bei Dou B1I and B3I dual-frequency signals. Taking the relevance of B1I and B3I signals into consideration,the algorithm adds a Kalman filter between the phase detector and carrier loop filter of the traditional dual-frequency independent tracking loop. The output results of the phase detectors of the B1I and B3I branches are then combined and filtered by the Kalman filter,and the results are input to the carrier loop filters of the corresponding branches. Proved by experiments,the algorithm not only enables the loop to enter a stable tracking state quickly,but also reduces the noise bandwidth of the two loop filters by about 10 Hz with the same tracking performance obtained.
基金
supported by the National Natural Science Foundation of China (No.51505221)
the Nanjing University of Aeronautics and Astronautics Graduate Innovation Base (Lab) Open Fund (No.kfjj20190312)
