Localization Using Extended Kalman Filter based on Chirp Spread Spectrum Ranging

확장 Kalman 필터를 적용한 첩 신호 대역확산 거리 측정 기반의 위치추정시스템

  • Bae, Byoung-Chul (School of Information and Communication Engineering, Dongguk University) ;
  • Nam, Yoon-Seok (School of Information and Communication Engineering, Dongguk University)
  • 배병철 (동국대학교(경주) 정보통신공학부) ;
  • 남윤석 (동국대학교(경주) 정보통신공학부)
  • Received : 2012.03.08
  • Accepted : 2012.07.01
  • Published : 2012.07.25


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.


Supported by : 한국과학재단


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