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Unscented Kalman Filters for Attitude and Orbit Estimation of a Low Earth Orbit CubeSat
KTH, School of Electrical Engineering (EES), Space and Plasma Physics.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this paper two Unscented Kalman Filters (UKF) are implemented to solve the

estimation of a satellite's position in orbit and its orientation relative to Earth's Centered

Inertial frame. Their aim is to see if an absolute position accuracy of less than 1 km

and an orientation estimation to less than 1

0 are possible for a 3U CubeSat with GPS,

sun sensors, magnetometers and a star tracker as sensors.

The orbit UKF is based on a Runge Kutta 7(8)

th-order integration method for orbit

propagation. The dynamic model uses perturbational accelerations due to Earth's geopotential,

the gravity of the Moon and the Sun, atmospheric drag and solar pressure.

The state of the lter is identical to the observation vector and consists of position and

velocity vectors of the satellite. The GPS receiver is used for measurements. Emphasis

has been put on the sampling rate of the GPS receiver as its availability is constrained

by the satellite's power limitations. The state of the attitude UKF consists of an error

quaternion, angular velocities and magnetometer bias. The sun sensors, magnetometers

and the star tracker are used for measurements. Dierent sensor combinations have been

simulated with the purpose of determining their inuence on the estimated attitude.

The results of the simulations indicate that an absolute position error of less than

1 km is feasible for sampling times of 15 minutes or less (approximately 6 per orbit).

Furthermore an accuracy of less than 1

0 is achieved by using the star tracker for attitude

determination either alone or in combination with the other sensors.

Place, publisher, year, edition, pages
2015. , 75 p.
EES Examensarbete / Master Thesis, XR-EE-SPP 2014:005
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-160616OAI: diva2:790548
Educational program
Master of Science - Aerospace Engineering
Available from: 2015-02-25 Created: 2015-02-25 Last updated: 2015-02-25Bibliographically approved

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