Abstract:Error equations are established using un-differenced observables and the equivalent double-differenced observation equations of multiple different stations are derived from the equivalent transformation theory. Meanwhile, the satellite and receiver’s clock biases are both eliminated. According to more numbers and stronger correlation of the equivalent ambiguity in multi-baseline solution, we propose a partial ambiguity resolution (PAR) method, in which all equivalent ambiguity is first sorted in ascending order. Subsequently, the maximum variance ambiguity is eliminated in an iterative process, while the ratio test is used to find a subset of equivalent ambiguity, which can be fixed. We validate this method using data from 5 IGS stations. The results show that, PAR presented in this paper not only can improve the fixed rate and success rate of ambiguity resolution, but also can greatly improve the availability of the multi-baseline solution, and the coordinate accuracy of PAR has considerable consistency in that of FAR.