Error Modeling and Analysis of Inertial Measurement Unit Using Stochastic and Deterministic Techniques
The measurements provided by inertial measurement unit (IMU) are erroneous due to certain noise parameters which are needed to be taken into account because the corrupted data is of little practical value in inertial navigation systems (INS). By integrating the IMU data in navigation algorithm, these errors are accumulated, leading to significant drift in the attitude, position and velocity outputs. Several techniques have been devised for the error modeling of this error by way of Neural Networks (NNs), PSD, ARMA, etc. In this paper, the deterministic and stochastic approach is followed to model the noise parameters of a low cost IMU. The error parameters thus determined by using the both techniques help in the development of an effective navigation algorithm. Deterministic errors are calculated by the help of Up-Down Test and the Rate Table test. While the stochastic errors, which are more random in nature, are recognized using Power Spectral Density (PSD) Analysis and Allan Variance techniques.
Z. Ashraf and W. Nafees, "Error Modeling and Analysis of Inertial Measurement Unit Using Stochastic and Deterministic Techniques", Advanced Materials Research, Vols. 403-408, pp. 4447-4455, 2012