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Improving the computational efficiency of the ambiguity function algorithm
Abstract Techniques are described in this paper for improving the Ambiguity Function Method (AFM) for differential GPS positioning using phase observations, (a) that take advantage of optimal dual-frequency observable combinations to improve thereliability of the AFM, and (b) that significantly shorten the computation time necessary for the AFM. The procedure can be used for kinematic positioning applications if a Kalman filter predicted position is accurate enough as an initial position for the suggested AFM searching procedure, or pseudokinematic mode using say a triple-difference solution as an initial position for static positioning if the baseline length is short (typically <5km).
Improving the computational efficiency of the ambiguity function algorithm
Abstract Techniques are described in this paper for improving the Ambiguity Function Method (AFM) for differential GPS positioning using phase observations, (a) that take advantage of optimal dual-frequency observable combinations to improve thereliability of the AFM, and (b) that significantly shorten the computation time necessary for the AFM. The procedure can be used for kinematic positioning applications if a Kalman filter predicted position is accurate enough as an initial position for the suggested AFM searching procedure, or pseudokinematic mode using say a triple-difference solution as an initial position for static positioning if the baseline length is short (typically <5km).
Improving the computational efficiency of the ambiguity function algorithm
Han, Shaowei (author) / Rizos, Chris (author)
Journal of Geodesy ; 70
1996
Article (Journal)
English
BKL:
38.73
Geodäsie
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