Position Estimation of MBK system for non-Gaussian Underwater Sensor Networks
비가우시안 노이즈가 존재하는 수중 환경에서 MBK 시스템의 위치 추정

Dae-Hee Lee, Yeon-Mo Yang, Kyung Moo Huh
2013 Journal of the Institute of Electronics and Information Engineers  
This paper study the position estimation of MBK system according to the non-linear filter for non-Gaussian noise in underwater sensor networks. In the filter to estimate location, recently, the extended Kalman filter (EKF) and particle filter are getting attention. EKF is widely used due to the best algorithm in the Gaussian noise environment, but has many restrictions on the usage in non-Gaussian noise environment such as in underwater. In this paper, we propose the improved One-Dimension
more » ... cle Filter (ODPF) using the distribution re-interpretation techniques based on the maximum likelihood. Through the simulation, we compared and analyzed the proposed particle filter with the EKF in non-Gaussian underwater sensor networks. In the case of both the sufficient statistical sample and the sufficient calculation capacity, we confirm that the ODPF's result shows more accurate localization than EKF's result.
doi:10.5573/ieek.2013.50.1.232 fatcat:dbc3a2co3rcpxohuamnby5txra