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An Indoor Fusion Localization Method using Pedestrian Dead Reckoning

Volume 14, Number 10, October 2018, pp. 2343-2353
DOI: 10.23940/ijpe.18.10.p10.23432353

Qian Zhaoa, Peng Luanb, Huiqiang Wangb, Hongwu Lvb, Guangsheng Fengb, and Mao Tangc

aHarbin University of Commerce, Harbin, 150028, China
bHarbin Engineering University, Harbin, 150001, China
cScience and Technology Resource Sharing Service Center of Heilongjiang, Harbin, 150001, China

(Submitted on July 9, 2018; Revised on August 8, 2018; Accepted on September 15, 2018)

Abstract:

We study the indoor localization problem based on Pedestrian Dead Reckoning (PDR) by analyzing the causes of localization error during pedestrian walking. To optimize the PDR-based localization method, we firstly propose a step-sense indoor localization framework, namely, Stepsense, which can analyze the total acceleration of the accelerometer sensor and obtain the number of pedestrian steps using the peak detection. In the Stepsense framework, the step length is calculated by the difference between the acceleration peak and the trough. The 9DOF (Degree of Freedom) and 6DOF methods are invoked by double-check strategy to make the result of direction estimation more accurate. Secondly, the adaptive error model is used to correct the state of particles in the particle filter, in which map matching and RSS matching are integrated. Finally, both the Stepsense framework and the proposed fusion localization method are examined in detail through experiments.

 

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