실해역 환경에서 무인 잠수정의 초기 상태 정렬을 위한 GPS와 관성 항법 센서 기반 항법 정렬 알고리즘
GPS and Inertial Sensor-based Navigation Alignment Algorithm for Initial State Alignment of AUV in Real Sea
2
조회
0
다운로드
3
인용
0
참고문헌
키워드
초록
This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.
Abstract
This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.
참고문헌 (14)
- 이판묵, "USBL, DVL과 선수각 측정신호를 융합한 심해 무인잠수정의 항법시스템", 한국해양공학회지, 31(4), pp.315~323 (2017), 한국해양공학회
- 이종무, "간접 되먹임 필터를 이용한 관성센서 및 초음파 속도센서 기반의 수중 복합항법 알고리듬", 한국해양공학회지, 17(6), pp.83~90 (2003), 한국해양공학회
- 이판묵, "초음파 거리계를 이용한 무인잠수정의 수중 복합 항법시스템", 한국해양공학회지, 18(4), pp.33~39 (2004), 한국해양공학회
- 목성훈, "자율무인잠수정의 지형참조항법 연구", 제어.로봇.시스템학회 논문지, 19(8), pp.702~708 (2013), 제어·로봇·시스템학회[DOI]
- 목성훈, "영상기반 지형참조항법 성능분석", 제어.로봇.시스템학회 논문지, 23(4), pp.294~299 (2017), 제어·로봇·시스템학회[DOI]
- 박슬기, "Psi각 오차모델 기반 스트랩다운 관성 항법 시스템의 정렬 알고리즘", 제어.로봇.시스템학회 논문지, 17(2), pp.183~189 (2011), 제어·로봇·시스템학회
- 강현석, "확장칼만필터를 이용한 무인잠수정의 GPS 보조 추측항법 알고리즘 설계", 한국해양공학회지, 31(1), pp.28~35 (2017), 한국해양공학회[DOI]
- 박영식, "융합된 다중 센서와 EKF 기반의 무인잠수정의 항법시스템 설계", 제어.로봇.시스템학회 논문지, 22(7), pp.562~569 (2016), 제어·로봇·시스템학회[DOI]
- 윤인용, "센서 결합을 이용한 확장 칼만 필터 기반 자세 추정 방법", 전자공학회논문지, 54(2), pp.106~114 (2017), 대한전자공학회
- 유태석, "무인잠수정 센서 선정을 위한 복합항법 성능 분석", 한국해양공학회지, 28(6), pp.566~573 (2014), 한국해양공학회
- 강철우, "변형된 오일러각 기반의 칼만필터를 이용한 자세 추정 성능 향상", 제어.로봇.시스템학회 논문지, 14(9), pp.881~885 (2008), 제어·로봇·시스템학회
- 김규현, "관성 항법 센서와 도킹 유도 센서를 융합한무인잠수정의 도킹 유도 항법 알고리즘에 대한 연구", 제어.로봇.시스템학회 논문지, 25(7), pp.647~656 (2019), 제어·로봇·시스템학회[DOI]
- D. H. Titterton, "Strapdown Inertial Navigation Technology" (2004), IET
- T. I. Fossen, "Guidance and Control of Ocean Vehicles" (1994), John Wiley & Sons Inc.