제어로봇시스템학회:학술대회논문집
- 2000.10a
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- Pages.175-175
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- 2000
Sensor Fusion for Underwater Navigation of Unmanned Underwater Vehicle
무인잠수체의 수중항법을 위한 센서퓨전
Abstract
In this Paper we propose a navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with biases and measurement noise, are investigated with theoretically data from KRISO's AUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system comment)'used aboard underwater vehicle.
Keywords