A step-wise algorithm for heading estimation via a smartphone

Currently, pedestrian dead reckoning (PDR) is widely used in indoor positioning. Its principle is to recursively update the location of pedestrians by using the step count, step length and heading. To estimate the pedestrian heading, a common method in PDR is to utilize magnetometer measurements to estimate the heading of a smartphone. However, magnetometer is extremely vulnerable to magnetic interferences in indoor environments, resulting that magnetometer measurements are unreliable for heading estimation. Moreover, there is an offset angle between the device heading and the pedestrian heading, and the device heading may continuously change while the pedestrian heading keeps fixed. Therefore, the pedestrian heading cannot be simply replaced by the device heading. In this paper, we propose a step-wise method to accurately estimate the heading of a pedestrian who carries a smartphone at different positions. To be specific, the proposed method fuses the signals from the accelerometer, gyroscope and magnetometer of the smartphone to transform the device reference frame to the Earth reference frame, and then utilizes the horizontal angular velocities to establish an optimization problem, the analytical solution of which is obtained. Extensive simulations are carried out and confirm that the proposed method is more robust and more accurate than the existing algorithms.