Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Robust Airspeed Estimation of an Unpowered Gliding Vehicle by Using Multiple Model Kalman Filters

다중모델 칼만 필터를 이용한 무추력 비행체의 대기속도 추정

  • 진재현 (순천대학교 기계우주항공공학부) ;
  • 박정우 (KAIST 항공우주공학과 대학원) ;
  • 김부민 (경상대학교 기계항공공학부 대학원) ;
  • 김병수 (경상대학교 기계항공공학부, 항공기부품기술연구소) ;
  • 이은용 (국방과학연구소)
  • Published : 2009.08.01
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Abstract

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.

Keywords

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