For the use of inertial measurement unit（IMU） and Bluetooth low energy（BLE） to locate in mine environment

propose multiple input fusion Kalman filtering（MIFKF） algorithm. MIFKF uses tilt and yaw Kalman filtering to preprocess inertial measurement values

it also uses BLE to obtain trilateration estimates

it combines pretreatment with estimated values and optimizes them by MIFKF to locate the staff in mine

positioning precision is further improved with the help of Rauch-Tung-Striebel（RTS） smoother. Simulation results show that

compared to trilateration algorithm and the standard KF algorithm

MIFKF can effectively reduce the positioning error in the complex mine environment.