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 releva...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.展开更多
This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optima...This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optimal path-following strategy based on phase quality estimate function. The enhanced joint phase gradient estimator can accurately and effectively extract the phase gradient information of wrapped pixels from noisy interferograms, which greatly increases the performances of the proposed method. The optimal path-following strategy ensures that the proposed algorithm simultaneously performs noise suppression and phase unwrapping along the pixels with high-reliance to the pixels with low-reliance. Accordingly, the proposed algorithm can be predicted to obtain better results, with respect to some other algorithms, as will be demonstrated by the results obtained from synthetic data.展开更多
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)
文摘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(4120147961261033+2 种基金61461011)the Guangxi Natural Science Foundation(2014GXNSFBA118273)the Dean Project of Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing(GXKL061503)
文摘This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optimal path-following strategy based on phase quality estimate function. The enhanced joint phase gradient estimator can accurately and effectively extract the phase gradient information of wrapped pixels from noisy interferograms, which greatly increases the performances of the proposed method. The optimal path-following strategy ensures that the proposed algorithm simultaneously performs noise suppression and phase unwrapping along the pixels with high-reliance to the pixels with low-reliance. Accordingly, the proposed algorithm can be predicted to obtain better results, with respect to some other algorithms, as will be demonstrated by the results obtained from synthetic data.
