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Archiwum Fotogrametrii, Kartografii i Teledetekcji

Tytuł artykułu

Stochastic modelling and analysis of IMU sensor errors

Autorzy Zhao, Y.  Horemuz, M.  Sjöberg, L. E. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
EN The performance of a GPS/INS integration system is greatly determined by the ability of stand-alone INS system to determine position and attitude within GPS outage. The positional and attitude precision degrades rapidly during GPS outage due to INS sensor errors. With advantages of low price and volume, the Micro Electrical Mechanical Sensors (MEMS) have been wildly used in GPS/INS integration. Moreover, standalone MEMS can keep a reasonable positional precision only a few seconds due to systematic and random sensor errors. General stochastic error sources existing in inertial sensors can be modelled as (IEEE STD 647, 2006) Quantization Noise, Random Walk, Bias Instability, Rate Random Walk and Rate Ramp. Here we apply different methods to analyze the stochastic sensor errors, i.e. autoregressive modelling, Gauss-Markov process, Power Spectral Density and Allan Variance. Then the tests on a MEMS based inertial measurement unit were carried out with these methods. The results show that different methods give similar estimates of stochastic error model parameters. These values can be used further in the Kalman filter for better navigation accuracy and in the Doppler frequency estimate for faster acquisition after GPS signal outage.
Słowa kluczowe
PL IMU   integracja   dokładność   nawigacja   czujnik  
EN IMU   integration   accuracy   navigation   sensor   random  
Wydawca Zarząd Główny Stowarzyszenia Geodetów Polskich
Czasopismo Archiwum Fotogrametrii, Kartografii i Teledetekcji
Rocznik 2011
Tom Vol. 22
Strony 437--449
Opis fizyczny Bibliogr. 16 poz.
autor Zhao, Y.
  • Division of Geodesy and Geoinformatics, Royal Institute of Technology (KTH), SE-100 44 Stockholm, Sweden,
autor Horemuz, M.
  • Division of Geodesy and Geoinformatics, Royal Institute of Technology (KTH), SE-100 44 Stockholm, Sweden,
autor Sjöberg, L. E.
  • Division of Geodesy and Geoinformatics, Royal Institute of Technology (KTH), SE-100 44 Stockholm, Sweden,
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