In inertial based self-contained pedestrian positioning systems, because the drifts of the gyroscopes grow with time, it relies on the earth magnetic field to suppress the heading errors. However, the earth magnetic field suffers from severe interference in indoor scenarios, and the magnetometer itself has measurement errors, the above reasons have dramatically limited the performance of the magnetometer-aided heading error calibration. This paper proposes a magnetic-aided heading error calibration approach. Firstly, the magnetometer is calibrated according to the motion model of the pedestrian and the calibration coefficients obtained are used to improve the accuracy of heading derived by the magnetometer. On this basis, a proved Quasi-Static magnetic Field (QSF) detection approach is proposed to extract the usable magnetic information fed into Zero velocity UPdaTe (ZUPT)- aided Extended Kalman Filter (EKF) algorithm to conduct the heading calibration. The experiment results show that the 684 meter long walk only has a position error of less than 0.5 meter and heading error of 3.2 degrees, and the position error is less than 0.2% of the total walking distance. The results indicate that the performance of the proposed method is superior to the existing approach.