A Novel Fuzzy Pedestrian Dead Reckoning System for Indoor Positioning Using Smartphone

Li, Chao; Zheng, Jingwen; Jiang, Zhuqing; Liu, Xinmeng; Yang, Yuying; Zhang, Beihang

doi:10.1109/vtcfall.2015.7390800

Cited by 4 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the step length estimator based on the empirical step-length model, there are various proposals. By training large amounts of data to find variables related to the step length, statistical regression methods [24,25] were used to construct a step length model. However, these methods must spend a lot of time on training and the limited sample data used in training will directly affect the accuracy and generality of the step length model.…”

Section: Introductionmentioning

confidence: 99%

A Novel Step Length Estimator Based on Foot-Mounted MEMS Sensors

Zhu

Wang

2018

Sensors

View full text Add to dashboard Cite

Pedestrian Dead Reckoning (PDR)-based pedestrian navigation technology is an important part of indoor and outdoor seamless positioning services. To improve the performance of PDR, we have conducted research on a step length estimator. Firstly, based on the basic theory of inertial navigation, we analyze in detail the errors in traditional Strapdown Inertial Navigation Systems (SINSs) caused by the unique motion state of pedestrians. Then, according to the fact that the inertial data from the foot can directly reflect the gait characteristics, we conduct a step length estimator that does not rely on SINS. The experimental results show that accuracy of the proposed method is between 0.6% and 1.4% with a standard deviation of 0.25%.

show abstract

Section: Introductionmentioning

confidence: 99%