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akaturk Academic measurement

Article detail · 2013

Robust adaptive unscented Kalman filter for attitude estimation of pico satellites

YÖKSİS OpenAlex SJR Q1 JCR Q2 Citations 115 Top 1% Percentile 99.9% FWCI 174.55
Year
2013
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue International Journal of Adaptive Control and Signal Processing
  • Catalog match (ISSN) International Journal of Adaptive Control and Signal Processing
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

SUMMARY Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time. This study introduces a fault‐tolerant attitude estimation algorithm for pico satellites. The algorithm uses a robust adaptive UKF, which performs correction for the process noise covariance (Q‐adaptation) or measurement noise covariance (R‐adaptation) depending on the type of the fault. By the use of a newly proposed adaptation scheme for the conventional UKF algorithm, the fault is detected and isolated, and the essential adaptation procedure is followed in accordance with the fault type. The proposed algorithm is tested as a part of the attitude estimation algorithm of a pico satellite. Copyright © 2013 John Wiley & Sons, Ltd.

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Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

115 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. CENGİZ HACIZADE
  2. HALİL ERSİN SÖKEN ORTA DOĞU TEKNİK ÜNİVERSİTESİ
  3. DOĞA DOLAY ORTA DOĞU TEKNİK ÜNİVERSİTESİ
  4. ELİF YAREN ÖZEN ÇETİN ORTA DOĞU TEKNİK ÜNİVERSİTESİ