The ionosphere is one of the major error sources in Global Navigation Satellite System （GNSS） posi- tioning, navigation and timing. Estimating the ionospheric delays precisely is of great interest in the GNSS commun...The ionosphere is one of the major error sources in Global Navigation Satellite System （GNSS） posi- tioning, navigation and timing. Estimating the ionospheric delays precisely is of great interest in the GNSS community. To date, GNSS observables for ionospheric estimation are most commonly based on carrier phase smoothed code measurements. However, leveling errors, which affect the performance of ionospheric modeling and differential code bias （DCB） estimation, exist in the carrier phase smoothed code observations. Such leveling errors are caused by the multipath and the short-term variation of DCB. To reduce these leveling errors, this paper investigates and estimates the ionospheric delays based on carrier phase measurements without the leveling errors. The line-of-sight ionospheric observables with high precision are calculated using precise point positioning （PPP） techniques, in which carrier phase measurements are the principal observables. Ionosphere-free and UofC PPP models are applied and compared for their effectiveness to minimize the leveling errors. To assess the leveling errors, single difference of ionospheric observables for a short baseline is examined. Results show that carrier phase- derived ionospheric observables from PPP techniques can effectively reduce the leveling errors. Furthermore, we compared the PPP ionosphere estimation model with the conventional carrier phase smoothed code method to assess the bias consistency and investigate the biases in the ionospheric observables.展开更多
Global navigation satellite system(GNSS) comes with potential unavoidable application risks such as the sudden distortion or failure of navigation signals because its satellites are generally operated until failure. I...Global navigation satellite system(GNSS) comes with potential unavoidable application risks such as the sudden distortion or failure of navigation signals because its satellites are generally operated until failure. In order to solve the problems associated with these risks, receiver autonomous integrity monitoring(RAIM) and ground-based signal quality monitoring stations are widely used. Although these technologies can protect the user from the risks, they are expensive and have limited region coverage. Autonomous monitoring of satellite signal quality is an effective method to eliminate these shortcomings of the RAIM and ground-based signal quality monitoring stations; thus, a new navigation signal quality monitoring receiver which can be equipped on the satellite platform of GNSS is proposed in this paper. Because this satellite-equipped receiver is tightly coupled with navigation payload, the system architecture and its preliminary design procedure are first introduced. In theory, code-tracking loop is able to provide accurate time delay estimation of received signals. However, because of the nonlinear characteristics of the navigation payload, the traditional code-tracking loop introduces errors. To eliminate these errors, the dummy massive parallel correlators(DMPC) technique is proposed. This technique can reconstruct the cross correlation function of a navigation signal with a high code phase resolution. Combining the DMPC and direct radio frequency(RF) sampling technology, the satellite-equipped receiver can calibrate the differential code bias(DCB) accurately. In the meantime, the abnormities and failures of navigation signal can also be monitored. Finally, the accuracy of DCB calibration and the performance of fault monitoring have been verified by practical test data and numerical simulation data, respectively. The results show that the accuracy of DCB calibration is less than 0.1 ns and the novel satellite-equipped receiver can monitor the signal quality effectively.展开更多
文摘The ionosphere is one of the major error sources in Global Navigation Satellite System （GNSS） posi- tioning, navigation and timing. Estimating the ionospheric delays precisely is of great interest in the GNSS community. To date, GNSS observables for ionospheric estimation are most commonly based on carrier phase smoothed code measurements. However, leveling errors, which affect the performance of ionospheric modeling and differential code bias （DCB） estimation, exist in the carrier phase smoothed code observations. Such leveling errors are caused by the multipath and the short-term variation of DCB. To reduce these leveling errors, this paper investigates and estimates the ionospheric delays based on carrier phase measurements without the leveling errors. The line-of-sight ionospheric observables with high precision are calculated using precise point positioning （PPP） techniques, in which carrier phase measurements are the principal observables. Ionosphere-free and UofC PPP models are applied and compared for their effectiveness to minimize the leveling errors. To assess the leveling errors, single difference of ionospheric observables for a short baseline is examined. Results show that carrier phase- derived ionospheric observables from PPP techniques can effectively reduce the leveling errors. Furthermore, we compared the PPP ionosphere estimation model with the conventional carrier phase smoothed code method to assess the bias consistency and investigate the biases in the ionospheric observables.
基金supported by the National Basic Research Program of China(“973”Project)(Grant No.6132XX)the National Hi-Tech Research and Development Program of China(“863”Project)(Grant No.2015AA7054032)the National Natural Science Foundation of China(Grant No.60901017)
文摘Global navigation satellite system(GNSS) comes with potential unavoidable application risks such as the sudden distortion or failure of navigation signals because its satellites are generally operated until failure. In order to solve the problems associated with these risks, receiver autonomous integrity monitoring(RAIM) and ground-based signal quality monitoring stations are widely used. Although these technologies can protect the user from the risks, they are expensive and have limited region coverage. Autonomous monitoring of satellite signal quality is an effective method to eliminate these shortcomings of the RAIM and ground-based signal quality monitoring stations; thus, a new navigation signal quality monitoring receiver which can be equipped on the satellite platform of GNSS is proposed in this paper. Because this satellite-equipped receiver is tightly coupled with navigation payload, the system architecture and its preliminary design procedure are first introduced. In theory, code-tracking loop is able to provide accurate time delay estimation of received signals. However, because of the nonlinear characteristics of the navigation payload, the traditional code-tracking loop introduces errors. To eliminate these errors, the dummy massive parallel correlators(DMPC) technique is proposed. This technique can reconstruct the cross correlation function of a navigation signal with a high code phase resolution. Combining the DMPC and direct radio frequency(RF) sampling technology, the satellite-equipped receiver can calibrate the differential code bias(DCB) accurately. In the meantime, the abnormities and failures of navigation signal can also be monitored. Finally, the accuracy of DCB calibration and the performance of fault monitoring have been verified by practical test data and numerical simulation data, respectively. The results show that the accuracy of DCB calibration is less than 0.1 ns and the novel satellite-equipped receiver can monitor the signal quality effectively.
