In case of more than 50km baseline length, the correlation between receivers is reduced. Therefore, there are still some rooms for improvement of its positional accuracy. In this paper, the stochastic modeling of the ionospheric delay is applied and its effects are analyzed. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the medium or long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. The ionospheric delay is stochastically modeled by well-known 1st order Gauss-Markov process. And the correlation time and variation of 1st order Gauss-Markov process are calculated. This paper gives analyzed results of developed algorithm compared with commercial software and Bernese.