Unknown Input Observer-Based Filterings for Mobile Pedestrian Localization Using Wireless Sensor Networks

Author

Hwan Hur ; Hyo-Sung Ahn

Author_Institution

Center for Anal. Instrum. Dev., Korea Basic Sci. Inst., Daejeon, South Korea

Volume

14

Issue

8

fYear

2014

fDate

Aug. 2014

Firstpage

2590

Lastpage

2600

Abstract

This paper proposes a pedestrian localization technique using a wireless sensor network. An unknown input observer (UIO)-based Kalman filter and UIO-based H_∞ filter are newly derived for the pedestrian localization. The purpose of the developed filters is to ensure a decoupling of unknown acceleration inputs generated by motions of the pedestrian from the state estimation and to minimize the external disturbance effects. Through comparative simulation and experimental tests, we evaluate the performance of the developed filters.

Keywords

Kalman filters; pedestrians; wireless sensor networks; Kalman filter; UIO-based H∞ filter; acceleration input; external disturbance effect; mobile pedestrian localization; pedestrian motion; state estimation; unknown input observer; wireless sensor network; Acceleration; Kalman filters; Mathematical model; Noise; Noise measurement; Vectors; Wireless sensor networks; Pedestrian localization; unknown input observer-based $H_{infty}$ filter; unknown input observer-based Kalman filter; wireless sensor networks (WSNs);

fLanguage

English

Journal_Title

Sensors Journal, IEEE

Publisher

ieee

ISSN

1530-437X

Type

jour

DOI

10.1109/JSEN.2014.2312193

Filename

6774468