The safety of miners is of interest to all countries. In the event of a coal mine disaster, how to locate the miners remains the biggest and most urgent issue. The aim of this study is to propose a precise positioning method for underground mine environments to a low cost and with acceptable accuracy. During the research work, in-depth learning and analysis of current geolocation methods for indoor areas have been carried out: advantages, disadvantages and the level of suitability of each method for mine environment have been presented. A layered two-step Hidden Markov Model has been proposed to simulate human walking in underground mine environments and an improved Viterbi algorithm suitable for the model has been implemented. The result of the positioning accuracy is quite satisfying compared to other positioning methods in the same category. A small modification to the proposed model has been illustrated in the future work which makes it more suitable for different situations rather than that limited by assumptions. The proposed positioning method can be claimed to be quite suitable for underground mine environments to a low cost and with acceptable accuracy.