간접 되먹임 필터를 이용한 관성센서 및 초음파 속도센서 기반의 수중 복합항법 알고리듬

Underwater Hybrid Navigation Algorithm Based on an Inertial Sensor and a Doppler Velocity Log Using an Indirect Feedback Kalman Filter

  • 이종무 (한국해양연구원 해양시스템안전연구소) ;
  • 이판묵 (한국해양연구원 해양시스템안전연구소) ;
  • 성우제 (서울대학교 조선해양공학과)
  • 발행 : 2003.12.01

초록

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), and a Doppler velocity log (DVL), accompanied by a magnetic compass. The errors of inertial measurement units increase with time, due to the bias errors of gyros and accelerometers. A navigational system model is derived, to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 20. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors, and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o,f equations of motion of SAUV, using a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance, by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass, and a depth sensor. The error of the estimated position still slowly drifts in the horizontal plane, about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

키워드

참고문헌

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