Indoor Positioning Algorithm Based on Bluetooth and Pedometer

In order to achieve the function of personnel position supervision and recording in large indoor spaces through sensor signals, this paper proposed a fusion indoor localization method based on Bluetooth and pedometer. The current fingerprint data and pedometer data were got and the algorithm parameters were initialized. Initial prediction of positioning coordinate was finished by estimation of the pedometer scale and direction for the calculation of the variance value of the fingerprint positioning. The Kalman gain was calculated with the Kalman filter to correct the $d_{x}$ and $d_{y}$ directions. According to $d_{x}$ and $d_{y}$, the prediction data of the positioning coordinate was adjusted as the final positioning coordinate data to complete the indoor positioning. This algorithm integrates Bluetooth’s fingerprint data with pedometer’s inertial navigation data. Testing has shown that the positioning trajectory is smooth, with no jumping or deviation, achieving precise positioning effectively.