At present, a new type of cloud track has emerged in China. Cloud track has the advantages of low cost, low energy consumption and short construction period. This new type of cloud track requires precise positioning of track detection. In order to eliminate the position error of cloud track detection, a new type of track detection vehicle was designed, and a new SIN-GPS positioning algorithm based on double-layer bidirectional LSTM network was developed. Firstly, the construction and sensor parameters of the track detection vehicle was inod uced. Then, the traditional SIN-GPS positioning algorithm and its shortcomings was analyzed. If GPS signal disappeared, the positioning error was very large. a bi-directional LSTM algorithm was proposed to illustrate the dynamic learning and compensation of errors when GPS signals disappeared. Finally, the accuracy of the algorithm in different motion states of the cloud track detection vehicle with three groups of experiments was analyzed. The results of experiments show that LSTM algorithm is superior to traditional algorithms and other intelligent algorithms. It reveals that the error of LSTM is 79.8% smaller than that of SINS when the vehicle is moving. The error of SINS is smallest when the vehicle is static. When setting the speed threshold of 0.2 m/s, using LSTM algorithm when it is larger than this threshold, and directly using SINS when it is smaller, the most accurate location results can be obtained.