Using Known Base Vector Length as Quasi-Observation to Improve GPS Ambiguity Resolution
Lilong Liu, Lihong Jin, Wen Hongyan
Abstract
Lilong Liu, Lihong Jin, Wen Hongyan
Abstract
The least-square ambiguity decorrelation adjustment method(LAMBDA)is one of the most appropriate techniques for GNSS carrier phase ambiguity resolution. The LAMBDA method is an algorithm for searching the most likely integer ambiguity combination. Based on a floating least-squares estimation of integer ambiguities, it minimizes the quadratic norm of the residuals. In the paper the use of known base vector length during ambiguity resolution of arrier phase measurements is considered. The comparisons of correct ambiguity resolution probabilities in the cases when the base vector length information is used and unused are given.
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The least-square ambiguity decorrelation adjustment method(LAMBDA)is one of the most appropriate techniques for GNSS carrier phase ambiguity resolution. The LAMBDA method is an algorithm for searching the most likely integer ambiguity combination. Based on a floating least-squares estimation of integer ambiguities, it minimizes the quadratic norm of the residuals. In the paper the use of known base vector length during ambiguity resolution of arrier phase measurements is considered. The comparisons of correct ambiguity resolution probabilities in the cases when the base vector length information is used and unused are given.
Key concepts: Ambiguity resolution, Decorrelation, Ambiguity, Lambda, Algorithm, Mathematics, Least-squares function approximation, GNSS applications