Pilots or autonomous aircraft need to know where they are in relation to the environment. On board aircraft there are inertial sensors that are prone to drift which requires corrections by referencing against known items, places, or signals. One such method of referencing is with global navigation satellite systems, and others, that are highlighted in this work, are based on using visual sensors. In particular the use of Synthetic Aperture Radar is emerging as a viable alternative. To use radar images in qualitative or quantitative analysis they must be registered with geographical information. Position data on an aircraft or spacecraft is not sufficient to determine with certainty what or where it is one is looking at in a radar image without referencing other images over the same area. It is demonstrated in this thesis that a digital elevation model can be split up and classified into different types of radar scatterers. Different parts of the terrain yielding different types of echoes increases the amount of radar specific characteristics in simulated reference images. This work also presents an interpretation of the imaging geometry of SAR such that existing methods in Computer Vision may be used to estimate the position from which a radar image has been taken. This is a direct image matching without requiring registration that is necessary for other proposals of SAR-based navigation solutions. By determination of position continuously from radar images, aircraft could navigate independently of day light, weather, and satellite data.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-66303 |
| Date | January 2017 |
| Creators | Divak, Martin |
| Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0024 seconds