Lee, Jung Ho Shin, Beomju Lee, Seok Lee, Taikjin Kim, Jaehun Kim, Chulki Park, Jinwoo 2024-01-19T12:07:29Z 2024-01-19T12:07:29Z 2022-03-01 2014-09 2331-5911 https://pubs.kist.re.kr/handle/201004/115329 The step length estimation plays a key role in measuring the user's location on a PDR system. Although its importance becomes greater with a wide spread of smart phone, improving the accuracy of the step length estimation has been left as a task to be resolved yet. It is because many factors of an individual human movement on specific motion should be taken into account. Thus, various motions of human need to be figured out to improve the accuracy of step length estimation. In this paper, we propose a motion based step length estimation algorithm using sensory functions of a smart phone. In the proposed algorithm, the motions of user are identified using hybrid model of decision tree (DT), artificial neural network (ANN) and support vector machine (SVM). Map-based in-flight calibration is also employed to analyze the gait characteristic of user and enhance the step length estimation without any RF assist. In order to verify the performance of the proposed algorithm, we performed experiments on 5 subjects in indoor and demonstrated its improved accuracy on estimating the step length. English INST NAVIGATION A Step Length Estimation based on Motion Recognition and Adaptive Gait Cognition using as Smartphone Conference 1 27th International Technical Meeting of the Satellite-Division of the Institute-of-Navigation (ION GNSS), pp.243 - 249 27th International Technical Meeting of the Satellite-Division of the Institute-of-Navigation (ION GNSS) 243 249 US Tampa, FL 2014-09-08 PROCEEDINGS OF THE 27TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS 2014) 000356331200022 2-s2.0-84939243349