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Localization Using Extended Kalman Filter based on Chirp Spread Spectrum Ranging  

Bae, Byoung-Chul (School of Information and Communication Engineering, Dongguk University)
Nam, Yoon-Seok (School of Information and Communication Engineering, Dongguk University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.49, no.4, 2012 , pp. 45-54 More about this Journal
Abstract
Location-based services with GPS positioning technology as a key technology, but recognizing the current location through satellite communication is not possible in an indoor location-aware technology, low-power short-range communication is primarily made of the study. Especially, as Chirp Spread Spectrum(CSS) based location-aware approach for low-power physical layer IEEE802.15.4a is selected as a standard, Ranging distance estimation techniques and data transfer speed enhancements have been more developed. It is known that the distance measured by CSS ranging has quite a lot of noise as well as its bias. However, the noise problem can be adjusted by modeling the non-zero mean noise value by a scaling factor which corresponds to the change of magnitude of a measured distance vector. In this paper, we propose a localization system using the CSS signal to measure distance for a mobile node taken a measurement of the exact coordinates. By applying the extended kalman filter and least mean squares method, the localization system is faster, more stable. Finally, we evaluate the reliability and accuracy of the proposed algorithm's performance by the experiment for the realization of localization system.
Keywords
Chirp-Spread-Spectrum(CSS) ranging; Extended Kalman Filter(EKF); least mean square(LMS); IEEE802.15.4a; measurement bias; Localization;
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Times Cited By KSCI : 1  (Citation Analysis)
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