Suscripción a Biblioteca: Guest
Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones
Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

Volumes:
Volumen 51, 2019 Volumen 50, 2018 Volumen 49, 2017 Volumen 48, 2016 Volumen 47, 2015 Volumen 46, 2014 Volumen 45, 2013 Volumen 44, 2012 Volumen 43, 2011 Volumen 42, 2010 Volumen 41, 2009 Volumen 40, 2008 Volumen 39, 2007 Volumen 38, 2006 Volumen 37, 2005 Volumen 36, 2004 Volumen 35, 2003 Volumen 34, 2002 Volumen 33, 2001 Volumen 32, 2000 Volumen 31, 1999 Volumen 30, 1998 Volumen 29, 1997 Volumen 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v51.i3.50
pages 48-55

"Fuzzy" Estimating of the In-Flight Geometric Calibration Parameters

Alexander I. Tkachenko
International Research and Training Center of Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kyiv

SINOPSIS

The goal of this work is to study opportunities to improve an accuracy and reliability of in-flight geometric calibration of the spacecraft imaging complex using known and unknown landmarks. Here calibration is interpreted as making more precise the mutual angular position of onboard imaging camera and a star tracker in a spacecraft body. It is an obligatory part of an optical-electronic complex preparation for imaging and geo-referencing of ground objects. The received snapshots, the readings of star tracker and GPS are processed on the ground. In calibration the use is made of known and unknown landmarks. There exist methods of in-flight geometric calibration based on forming measuring equations of various physical origin. These equations are solved by the least square method. Usually snapshots of known landmarks are used but there could be problem solutions with unknown landmarks involved. This work suggests the approach to solving the in-flight geometric calibration problem using formulas of fuzzy observer rather than the least square method. In many cases such approach allows one to weaken the negative impact of disturbances and sensor errors onto accuracy of estimating calibration parameters. The essential feature of the observer realization process is its recursive character. The obtained estimates are made more precise not by a manifold of received snapshots at once, but by each snapshot successively. Such approach allows us to improve convergence of estimates. As in this case the estimated parameters of calibration are constant there is no need for a stage of prognosis peculiar for such algorithm and only update procedure is used. Presentation and arguments are provided with a sufficient volume of computer simulation and analysis of its results. They confirm the above mentioned advantages of fuzzy observer as compared with the least square method for in-flight geometric calibration.

REFERENCIAS

  1. Tkachenko A.I., On in-flight alignment of optical-electronic complex of space craft, Izvestiya RAN. Teoriya i sistemy upravleniya, 2013, No. 6, 122-130, DOI: 10.7868/S0002338813060127.

  2. Lebedev D.V., In-flight geometric calibration of optoelectronic equipment of remote sensing satellite by unknown landmarks, Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki, 2013, No.5, 114-125.

  3. Lobanov A.N., Photogrammetry [in Russian], Nedra, Moscow, 1984.

  4. Tkachenko A.I., On the problem of in-flight geometric calibration using unknown landmarks, Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki", 2014, No. 1, 129-138.

  5. Tkachenko A.I., Improvement of procedure of in-flight geometric calibration using unknown landmarks, Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki", 2017, No. 2, 112-121.

  6. Lebedev D.V., Tkachenko A.I., Information and algorithmic aspects of moving objects control [in Russian], Naukova dumka, Kiev, 2000.

  7. Bakan G.M., Algorithms for constructing guaranteed and fuzzy ellipsoid estimates based on the least square methods, Problemy upravleniya i informatiki, 1995, No. 3, 117-129.

  8. Golovin A.A., Mironovskiy L.A., Algorithmic control of Kalman filter, Avtomatika i telemekhanika, 1993, No.7, 173-185.

  9. Tkachenko A.I., On geo-referencing of ground objects by space snapshots, Kosmichna nauka i tekhnologiya, 2015, 21, No. 2, 65-72.

  10. Tkachenko A.I., Two algorithms of ground objects referencing by space snapshots, Kosmichna nauka i tekhnologiya, 2018, 24, No. 3, 69-74.

  11. Tkachenko A.I., Algorithms of the attitude matching of star tracker and camera of spacecraft, Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki", 2015, No. 3, 116-126.


Articles with similar content:

Algorithms of the Attitude Matching of Star Tracker and Camera of Spacecraft
Journal of Automation and Information Sciences, Vol.47, 2015, issue 5
Alexander I. Tkachenko
Geo-referencing of a Ground Object Using Inexact Space Snapshots
Journal of Automation and Information Sciences, Vol.48, 2016, issue 8
Alexander I. Tkachenko
A Combined Algorithm of the In-Flight Geometric Calibration Using Unknown Landmarks
Journal of Automation and Information Sciences, Vol.51, 2019, issue 1
Alexander I. Tkachenko
Spacecraft Attitude Control Using the Magnetic-GPS Dataware System. Part I
Journal of Automation and Information Sciences, Vol.33, 2001, issue 1
Dmitriy V. Lebedev, Alexander I. Tkachenko
Optimal Quadrature Formulas for Computation of Continuous Wavelet Transforms of Functions in Certain Classes
Journal of Automation and Information Sciences, Vol.42, 2010, issue 5
Valeriy K. Zadiraka, Svetlana S. Melnikova, Liliya V. Luts