This paper deals with the problem of determining the baseline vector between two GPS receivers in single frequency (L1) using the basic principles of interferometric Differential GPS, therefore using the interferometric relations between the two receivers and the satellites visible to both receivers. As a preliminary step, ambiguity identification was solved using the results provided by the Kalman filter; these results were optimized by evaluating the Dilution Of Precision indexes for satellites in view of the receivers. Results achieved by applying this first procedure to data collected are discussed. To increase the accuracy of the results, a new, computationally fast algorithm for carrier phase ambiguity resolution on data collected from static and dynamics acquisitions was developed, implemented and tested. The new algorithm permitted an increase of accuracy of about two orders of magnitude with respect to results given by filtered Double Difference in the resolution of baseline vector.
F. Piergentili, E. Cordelli (2010). A New Method For DGPS Ambiguity Resolution. JOURNAL OF NAVIGATION, 63, 645-661 [10.1017/S0373463310000299].
A New Method For DGPS Ambiguity Resolution
PIERGENTILI, FABRIZIO;
2010
Abstract
This paper deals with the problem of determining the baseline vector between two GPS receivers in single frequency (L1) using the basic principles of interferometric Differential GPS, therefore using the interferometric relations between the two receivers and the satellites visible to both receivers. As a preliminary step, ambiguity identification was solved using the results provided by the Kalman filter; these results were optimized by evaluating the Dilution Of Precision indexes for satellites in view of the receivers. Results achieved by applying this first procedure to data collected are discussed. To increase the accuracy of the results, a new, computationally fast algorithm for carrier phase ambiguity resolution on data collected from static and dynamics acquisitions was developed, implemented and tested. The new algorithm permitted an increase of accuracy of about two orders of magnitude with respect to results given by filtered Double Difference in the resolution of baseline vector.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.