An indoor fusion localization method using pedestrian dead reckoning????(Open Access)

作者：Zhao, Qian^*; Luan, Peng; Wang, Huiqiang; Lv, Hongwu; Feng, Guangsheng; Tang, Mao

来源：International Journal of Performability Engineering, 2018, 14(10): 2343-2353.

DOI：10.23940/ijpe.18.10.p10.23432353

• Accelerometer sensor
• Direction estimation
• Indoor localization
• Localization method
• Map matching
• Particle filter
• Pedestrian dead reckoning (PDR)
• Pedestrian dead reckonings

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.

• 出版日期2018
• 单位哈尔滨工程大学