Abstract
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 how Map Matching (MM) and Map Aiding (MA) methods constrain the navigation solution through an auxiliary particle filter. Previous studies examined each method individually, but the combination provides a more accurate position estimation. Additionally, this research introduces 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 practical scenarios.
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Yu, C., Lan, H., Liu, Z., El-Sheimy, N., Yu, F. (2016). Indoor Map Aiding/Map Matching Smartphone Navigation Using Auxiliary Particle Filter. In: Sun, J., Liu, J., Fan, S., Wang, F. (eds) China Satellite Navigation Conference (CSNC) 2016 Proceedings: Volume I. Lecture Notes in Electrical Engineering, vol 388. Springer, Singapore. https://doi.org/10.1007/978-981-10-0934-1_29
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DOI: https://doi.org/10.1007/978-981-10-0934-1_29
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