Abstract: In order to further improve the positioning accuracy of personnel in underground coal mine , Salp Swarm Algorithm is introduced in this paper for location estimation. The algorithm is easy to calculate with a simple structure and able to improve the initial random solutions effectively and converge towards the optimum. When dealing with the nonlinear equations obtained from the measurement data of four UWB base stations, Salp Swarm Algorithm does not eliminate the common quadratic variables as the least square method does, but uses the original overdetermined equations to find the optimal solution, which is also an important reason why the Salp Swarm Algorithm has a higher resolution accuracy than the least square method. The simulation results show that the Salp Swarm Algorithm performs better than the least square method in the 3D location calculation based on the distance and azimuth of the target.