Adaptive Tuning of the Unscented Kalman Filter for Satellite Attitude Estimation

Soken H. E., Sakai S.

JOURNAL OF AEROSPACE ENGINEERING, cilt.28, sa.3, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 3
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1061/(asce)as.1943-5525.0000412
  • Dergi Adı: JOURNAL OF AEROSPACE ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: Attitude estimation, Adaptive unscented Kalman filtering (UKF), Process noise covariance, Magnetometer bias
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

Determining the process noise covariance of the unscented Kalman filter (UKF) is a difficult procedure. The analytical approximation method gives satisfactory results in certain cases, but it fails when generalized for the estimation of the extended states, such as the case that sensor biases or scale factors are included in the state vector. The main aim of this research is to find an appropriate tuning algorithm for the process noise covariance of the UKF when the magnetometer biases are estimated, as well as attitude and gyro biases. In this sense, an adaptive tuning method for an UKF that is used for satellite attitude estimation is given and the adaptive UKF algorithm is tested in various scenarios for the attitude and sensor bias estimation. The given adaptation method is an easy way of tuning the filter, especially in the absence of any analytical approximation for the calculation of the process noise covariance, and the performed simulations show that by using the adaptive UKF, it is possible to get accurate estimates that are close to optimal. (C) 2014 American Society of Civil Engineers.