<p>Man portable air defence systems, MANPADS, pose a big threat to civilian and military aircraft. This thesis aims to find methods that could be used in a missile approach warning system based on infrared cameras.</p><p>The two main tasks of the completed system are to classify the type of missile, and also to estimate its position and velocity from a sequence of images.</p><p>The classification is based on hidden Markov models, one-class classifiers, and multi-class classifiers.</p><p>Position and velocity estimation uses a model of the observed intensity as a function of real intensity, image coordinates, distance and missile orientation. The estimation is made by an extended Kalman filter.</p><p>We show that fast classification of missiles based on radiometric data and a hidden Markov model is possible and works well, although more data would be needed to verify the results.</p><p>Estimating the position and velocity works fairly well if the initial parameters are known. Unfortunately, some of these parameters can not be computed using the available sensor data.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-57147 |
| Date | January 2010 |
| Creators | Holm Ovrén, Hannes, Emilsson, Erika |
| Publisher | Linköping University, Department of Electrical Engineering, Linköping University, Department of Electrical Engineering |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, text |
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