Modeling Inertial Sensor Errors Using Autoregressive (AR) Models

S. Nassar, K-P. Schwarz, N. El-Sheimy and A. Noureldin

Abstract:	The accelerometer and gyro sensor errors of a Strapdown Inertial Navigation System (SINS) consist of two parts: a deterministic part and a random part. The deterministic part includes biases and scale factors, which are determined by calibration and then removed from the raw measurements. The random part is correlated over time and is basically due to the variations in the SINS sensor bias terms. Therefore, these errors are modeled stochastically so that they can be included in the SINS error model. For most of the navigation-grade SINS systems, a first-order Gauss-Markov model with a fairly large correlation time is usually used to describe the random errors associated with inertial sensors. By studying the autocorrelation sequences of the noise components at the outputs of inertial sensors, we have determined that a first-order Gauss-Markov is not adequate to model such noise behavior. This paper offers a new method to model the inertial sensor noise as a higher order autoregressive (AR) process and adaptively estimates the AR model parameters. Three different methods of determining the AR model parameters are investigated, namely: the Yule-Walker (autocorrelation) method, the covariance method and the Burg’s method. The three algorithms were tested with different AR model orders with real SINS static data. The results showed that the Burg’s method gives the minimum prediction mean square estimation error and hence this method was used for generating the applied AR models. In this paper, the current algorithms for modeling inertial sensor errors are introduced. The different algorithms for AR modeling are discussed and their results are presented. The results after applying the Burg’s AR models with different orders are also analyzed.
Published in:	Proceedings of the 2003 National Technical Meeting of The Institute of Navigation January 22 - 24, 2003 Disneyland Paradise Pier Hotel Anaheim, CA
Pages:	116 - 125
Cite this article:	Updated citation: Published in NAVIGATION: Journal of the Institute of Navigation
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