인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.17 No.2
- 발행연도
- 2017.6
- 수록면
- 121 - 128 (8page)
- DOI
- 10.5391/IJFIS.2017.17.2.121
이용수
초록· 키워드
In this paper, we propose a fusion algorithm of multifarious and multiple sensors to enhance the accuracy and reliability of position and velocity estimation for the vehicles. We proposed an adaptive Kalman filter for multiple sensor fusion to provide a fault tolerant estimation. We verified the multiple sensor fusion estimator can provide a fault tolerant estimation through Matlab simulation and laboratory equipped experiments. We also proposed a fusion algorithm of multifarious sensors in order to enhance the velocity estimation accuracy. We proposed a Kalman filter error correction for compensate the accumulative error in the main sensor with the other type of sensor which has characteristic of biased error. We also developed a fusion algorithm for compensate the error in the position measuring with the velocity measuring. We made experiments for estimating position and velocity of vehicle simultaneously through the fusion of multifarious and multiple sensors and showed that average position error was 1.5764 m and average velocity accuracy was 99.81%.
#Position estimation
#Velocity estimation
#Kalman filter
#Sensor fusion
#Map based GPS error correction
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목차
- Abstract
- 1. Introduction
- 2. Multiple Sensor Fusion Model
- 3. Multifarious Sensor Fusion Model
- 4. Map based GPS Error Correction
- 5. Position and Velocity Estimation and Experiments
- 6. Conclusions
- References
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-ECN-0101-2018-003-001014471
