Title :
State space modeling of random drift rate in high-precision gyro
Author :
Jiang Hong ; Yang Wei-Qin ; Yang You-Tang
Author_Institution :
Dept. of Autom. Control, Beijing Inst. of Technol., China
fDate :
7/1/1996 12:00:00 AM
Abstract :
A state space approach for the modeling of nonstationary time series is presented. Based on the concept of smoothness priors constraint, the overall model is fitted by using the Kalman filler and Akaike´s AIC criterion. Whenever an autoregressive (AR) model with time-varying coefficient is fitted in state space model, it can be used for the time-varying spectrum estimation. Some numerical results of gyro drift models are obtained for analysis of high-precision gyro. As the trend, irregular and periodic components of the observed time series can be modeled simultaneously, it is statistically more accurate and efficient than that modeled separately.
Keywords :
Kalman filters; autoregressive processes; fault diagnosis; gyroscopes; inertial navigation; parameter estimation; random processes; state-space methods; time series; time-varying systems; AIC criterion; Akaike; Kalman filler; autoregressive model; fault monitoring; gyro drift models; high-precision gyro; nonstationary time series; numerical results; observed time series; random drift rate; smoothness; state space modeling; time-varying coefficient; time-varying spectrum estimation; Bayesian methods; Control theory; Difference equations; Estimation error; Fault detection; Fault diagnosis; Mechanical engineering; Robust control; Spectral analysis; State-space methods;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
