The majority of WiFi positioning methods use several access points to estimate users locations. But different interferences such as walls, some obstacles, signal reflection make it sometimes impossible to use several access points. Moreover, private and public places where WiFi positioning can be useful homes, cafes, malls have only one access point covering almost all of the space. So it is crucial to make positioning only with one access point because it will release us from quantitative restriction and make WiFi positioning available in all public and private places. Several probabilistic methods exist to determine the position of the user from the input of the signal strength sequence. We used statistical models as Markov Chains to track users paths. You can see the results of experiments in real-life premises.