  Kalman filter-based Inertial Navigation System (INS) is a reliable and
efficient method to estimate the position of a pedestrian indoors. Classical
INS-based methodology which is called IEZ (INS-EKF-ZUPT) makes use of an
Extended Kalman Filter (EKF), a Zero velocity UPdaTing (ZUPT) to calculate the
position and attitude of a person. However, heading error which is a key factor
of the whole Pedestrian Dead Reckoning (PDR) system is unobservable for
IEZ-based PDR system. To minimize the error, Electronic Com-pass (EC) algorithm
becomes a valid method. But magnetic disturbance may have a big negative effect
on it. In this paper, the Quasi-static Magnetic field Detection (QMD) method is
proposed to detect the pure magnetic field and then selects EC algorithm or
Heuristic heading Drift Reduction algorithm (HDR) according to the detection
result, which implements the complementation of the two methods. Meanwhile, the
QMD, EC, and HDR algorithms are integrated into the IEZ framework to form a new
PDR solution which is named Advanced IEZ (AIEZ).
