|Abstract:||This paper presents a technique to accurately estimate the states of a small autonomous helicopter using a combination of gyroscopes, accelerometers, and GPS. State estimation is performed by using indirect Kalman filtering based on sensor modeling and error dynamics, not helicopter modeling. The number of measurements available to the Kalman filter is nine: three attitude rates from the gyroscopes, three accelerations, and three position measurements (x, y, z) from the GPS. The Kalman filter is decomposed into two loosely coupled filters — one for attitude and the other for position estimation for fast computation.|
|Published in:||NAVIGATION, Journal of the Institute of Navigation, Volume 56, Number 2|
|Pages:||73 - 82|
|Cite this article:||
Jun, Myungsoo, "State Estimation for Autonomous Helicopter via Sensor Modeling", NAVIGATION, Journal of The Institute of Navigation, Vol. 56, No. 2,
2009, pp. 73-82.
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