- Tytuł:
- Stochastic modelling and analysis of IMU sensor errors
- Autorzy:
-
Zhao, Y.
Horemuz, M.
Sjöberg, L. E. - Powiązania:
- https://bibliotekanauki.pl/articles/130312.pdf
- Data publikacji:
- 2011
- Wydawca:
- Stowarzyszenie Geodetów Polskich
- Tematy:
-
IMU
integration
accuracy
navigation
sensor
random
integracja
dokładność
nawigacja
czujnik - Opis:
- 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.
- Źródło:
-
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2011, 22; 437-449
2083-2214
2391-9477 - Pojawia się w:
- Archiwum Fotogrametrii, Kartografii i Teledetekcji
- Dostawca treści:
- Biblioteka Nauki
Artykuł