State space modeling of random drift rate in high-precision gyro

被引：19

作者：

Hong, J ^{[1
]}

Yang, WQ ^{[1
]}

Yang, YT ^{[1
]}

机构：

[1] TSING HUA UNIV,DEPT PRECIS INSTRUMENT & MECHANOL,BEIJING 100084,PEOPLES R CHINA

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 1996年 / 32卷 / 03期

关键词：

D O I：

10.1109/7.532273

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

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.

引用

页码：1138 / 1143

页数：6

共 10 条

[1]

Akaike H., 1980, Bayes statistics, P141

[2]

Anderson B. D. O., 1979, OPTIMAL FILTERING

[3]

BROTHERTON T, P 20 IEEE C DEC CONT, P1061

[4]

JIANG H, 1993, 5 CHIN S CONTR THEOR, P305

[5]

Kitagawa G., 1981, Journal of Time Series Analysis, V2, P103, DOI 10.1111/j.1467-9892.1981.tb00316.x

[6] A SMOOTHNESS PRIORS TIME-VARYING AR COEFFICIENT MODELING OF NONSTATIONARY COVARIANCE TIME-SERIES [J].

KITAGAWA, G ;

GERSCH, W .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1985, 30 (01) :48-56

[7] A SMOOTHNESS PRIORS STATE-SPACE MODELING OF TIME-SERIES WITH TREND AND SEASONALITY [J].

KITAGAWA, G ;

GERSCH, W .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1984, 79 (386) :378-389

[8]

SHILLER R, ECONOMETRICA, V41, P775

[9]

YANG WQ, 1993, 5 CHIN S CONTR THEOR, P553

[10]

YANG YT, 1988, TH88020 TSHINGH U

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