ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 Observability and Estimation Error Analysis of the Initial Fine Alignment Filter for Nonleveling Strapdown Inertial Navigation System
Cited 22 time in scopus Download 0 time Share share facebook twitter linkedin kakaostory
저자
조성윤, 이형근, 이흥규
발행일
201303
출처
Journal of Dynamic Systems, Measurement, and Control, v.135 no.2, pp.1-9
ISSN
0022-0434
출판사
American Society of Mechanical Engineers(ASME)
DOI
https://dx.doi.org/10.1115/1.4007552
협약과제
11VC2200, 운전 안전성 및 편의성 향상을 위한 운전자 시야 중심 차량용 증강현실 정보제공 시스템 기술개발, 김경호
초록
In this paper, performance of the initial fine alignment for the stationary nonleveling strapdown inertial navigation system (SDINS) containing low-grade gyros is analyzed. First, the observability is analyzed by conducting a rank test of an observability matrix and by investigating the normalized error covariance of the extended Kalman filter based on the ten-state model. The results show that the accelerometer biases on horizontal axes are unobservable. Second, the steady-state estimation errors of the state variables are derived using the observability equation. It is verified that the estimates of the state variables have errors due to the unobservable state variables and nonleveling attitude angles of a vehicle containing the SDINS. Especially, this paper shows that the larger the attitude angles of the vehicle are, the greater the estimation errors are. Finally, it is shown that the performance of the eight-state model excluding the two unobservable state variables is better than that of the ten-state model in the fine alignment by a Monte Carlo simulation. © VC 2012 by ASME.
키워드
estimation error, extended Kalman filter, initial fine alignment, observability, SDINS
KSP 제안 키워드
Attitude angles, Error analysis, Extended kalman fiLTEr, Low-grade, Monte-Carlo simulation(MCS), Rank test, State Model, State variables, Strapdown inertial navigation system(SINS), error covariance, estimation error