Improving micro-electro-mechanical inertial navigation system based indoor pedestrian localization is a hot and hard topic these days. It is because random errors of MEMS gyroscopes and accelerators are very complicated

and very difficult to model using norm techniques. In this paper

a map matching method based on conditional random fields and indoor 3D map is proposed. The algorithm is designed by establishing the mathematical relationship between the inertial position and the interior points of indoor map

and the optimal trajectory algorithm is used to get the estimated locations. The position errors of inertial navigation are corrected according to the matching points solved by the algorithm.