Research on the algorithm for estimating parameters of the linear error model of micromechanical strapdown inertial navigation system
Аuthors
*,Bauman Moscow State Technical University, Moscow, Russian Federation
*e-mail: amas@bmstu.ru
Abstract
The algorithm for estimating the parameters of a linear error model for a low-accuracy micromechanical strapdown inertial navigation system is considered. The estimated error model parameters are accelerometer biases and gyroscope drifts. The estimation algorithm is based on Kalman filtering. The paper considers a variant of the estimation algorithm that utilizes two Kalman filters: the first is used for smoothing measurements obtained from accelerometers and gyroscopes, and the second one for estimating the SINS error model parameters. The research of the algorithm involves analyzing the behavior of estimating the strapdown inertial navigation system error model parameters for various algorithm configurations. An algorithm with a full and reduced state vector for one of the Kalman filters is considered, and the behavior of the estimation is investigated for various ratios of the covariance matrices of the input and measurement noises of both Kalman filters, including the case of a non-stationary strapdown inertial navigation system rotation. The results obtained during the simulation demonstrate the fundamental applicability of the considered algorithm and illustrate the behavior of the estimation process under various conditions.
Keywords:
error model, SINS, MEMS, Kalman filter, navigation algorithmReferences
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