An Adaptive Heading Estimation Method based on Holding Styles Recognition Using Smartphone Sensors


  • Khanh Nguyen-Huu Dalat University
  • Ninh Duong-Bao Hunan University
  • Luong Nguyen Thi Dalat University
  • Le Do Thi Dalat University
  • Thuy Huynh Thi Thu Dalat University
  • Seon-Woo Lee Hallym University



Adaptive Heading Estimation Method, Holding Styles Recognition, Smartphone Sensors


Pedestrian Dead Reckoning (PDR), which comes with many sensors integrated into widely available smartphones, is known as one of the most popular indoor positioning techniques. Sensors such as accelerometers, gyroscopes, and magnetometers are used to determine three important components in PDR: step detection, step length estimation, and heading estimation. Among them, the last component is the most challenging since a small heading error accumulates to produce a very large positioning error, especially when the pedestrian holds the smartphone in unconstrained styles such as swinging the phone freely along the pedestrian’s walking direction or putting the phone into the pants’ front pockets. The research proposes an adaptive heading estimation method to deal with heading errors caused by smartphone holding styles. The novelties are described as follows. Firstly, the proposed method attempts to classify the four basic smartphone holding styles using a machine learning algorithm based on simple features of acceleration values to give pedestrians more freedom during the walking period. Secondly, the proposed method adaptively combines the two heading estimation methods, which are calculated from the integrated sensors, to determine the walking direction for different smartphone holding styles. The experimental results show that the proposed heading estimation method achieves average heading errors of less than 30 degrees when testing in two different walking paths with the smartphone held in dynamic styles. It helps to reduce the heading errors by more than 15% compared to previous heading estimation methods.


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Author Biographies

Khanh Nguyen-Huu, Dalat University

Department of Electronics & Telecommunications

Ninh Duong-Bao, Hunan University

College of Computer Science and Electronic Engineering

Luong Nguyen Thi, Dalat University

Faculty of Information Technology

Le Do Thi, Dalat University

Department of Electronics & Telecommunications

Thuy Huynh Thi Thu, Dalat University

Department of Electronics & Telecommunications

Seon-Woo Lee, Hallym University

Division of Software


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