Adaptive Modified Wave Estimator

Author

Ersoy, Yetkin ; Efe, Murat

Author_Institution

Muhendislik Fakultesi Elektron. Muh. Bolumu, Ankara Univ.

fYear

2006

fDate

17-19 April 2006

Firstpage

1

Lastpage

4

Abstract

Kalman filter is frequently used for integration of the navigation systems. Process noise variance, employed in the calculation of the Kalman filter´s state prediction covariance, determines error estimation capability of the filter for navigation system. Due to the difficulties in exact modelling, i.e., determining the exact value of the process noise, Kalman filter´s performance could become limited. Recently, modified wave estimator (MWE) has been suggested for the state estimation of especially weakly observed states with high accuracy. Unfortunately, due to cycle time calculations, computational burden of the MWE is very high. In this paper, adaptive modified wave estimator is suggested in order to overcome the computation issue. Estimation performance and computational burden of, Kalman filter, MWE and AMWE are discussed for a selected navigation application

Keywords

adaptive Kalman filters; covariance analysis; inertial navigation; noise; state estimation; AMWE; Kalman filter; adaptive modified wave estimator; navigation system; process noise variance; state estimation; state prediction covariance; Computational modeling; Error analysis; Influenza; Kalman filters; Navigation; State estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications, 2006 IEEE 14th

Conference_Location

Antalya

Print_ISBN

1-4244-0238-7

Type

conf

DOI

10.1109/SIU.2006.1659922

Filename

1659922