A map-based pedestrian navigation method is presented in this research,integrating indoor map information and MEMS-based inertial sensors to enhance the performance of pedestrian indoor navigation.This paper demonstrates howMap Matching and Map Aiding methods constrain the navigation solution through an auxiliary particle filter.Previous studiesexamined each method individually,but the combination provides a more accurate position estimation.Additionally,this researchintroduces a novel cascade structure filter algorithm to reduce the computational burden and improve the estimation speed of APF by decreasing the update frequency of APF.The accuracy and availability of the proposed algorithm are tested and validated by performing experiments in various practicalscenarios.