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http://dx.doi.org/10.5139/JKSAS.2012.40.2.108

A Performance Comparison of Nonlinear Kalman Filtering Based Terrain Referenced Navigation  

Mok, Sung-Hoon (KAIST 항공우주공학전공 대학원)
Bang, Hyo-Choong (KAIST 항공우주공학)
Yu, Myeong-Jong (국방과학연구소)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.40, no.2, 2012 , pp. 108-117 More about this Journal
Abstract
This paper focuses on a performance analysis of TRN among various nonlinear filtering methods. In a TRN research, extended Kalman filter(EKF) is a basic estimation algorithm. In this paper, iterated EKF(IEKF), EKF with stochastic linearization(SL), and unscented Kalman filter(UKF) algorithms are introduced to compare navigation performance with original EKF. In addition to introduced sequential filters, bank of Kalman filters method, which is one of the batch method, is also presented. Finally, by simulating an artificial aircraft mission, EKF with SL was chosen as the most consistent filter in the introduced sequential filters. Also, results suggested that the bank of Kalman filters can be alternative for TRN, when a fast convergence of navigation solution is needed.
Keywords
Terrain Referenced Navigation; Extended Kalman Filter; Stochastic Linearization; Unscented Kalman Filter; Bank of Kalman Filters;
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