liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Navigation and SAR Auto-focusing in a Sensor Fusion Framework
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2011 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

Since its discovery, in the 1940's, radar (Radio Detection and Ranging) has become an important ranging sensor in many areas of technology and science. Most of the military and many civilian applications are unimaginable today without radar. With technology development, radar application areas have become larger and more available. One of these applications is Synthetic Aperture Radar (SAR), where an airborne radar is used to create high resolution images of the imaged scene. Although known since the 1950's, the SAR methods have been continuously developed and improved and new algorithms enabling real-time applications have emerged lately. Together with making the hardware components smaller and lighter, SAR has become an interesting sensor to be mounted on smaller unmanned aerial vehicles (UAV's). One important thing needed in the SAR algorithms is the estimate of the platform's motion, like position and velocity. Since this estimate is always corrupted with errors, particularly if lower grade navigation system, common in UAV applications, is used, the SAR images will be distorted. One of the most frequently appearing distortions caused by the unknown platform's motion is the image defocus. The process of correcting the image focus is called auto-focusing in SAR terminology. Traditionally, this problem was solved by methods that discard the platform's motion information, mostly due to the off-line processing approach, i.e. the images were created after the flight. Since the image (de)focus and the motion of the platform are related to each other, it is possible to utilise the information from the SAR images as a sensor and improve the estimate of the platform's motion. The auto-focusing problem can be cast as a sensor fusion problem. Sensor fusion is the process of fusing information from different sensors, in order to obtain best possible estimate of the states. Here, the information from sensors measuring platform's motion, mainly accelerometers, will be fused together with the information from the SAR images to estimate the motion of the flying platform. Two different methods based on this approach are tested on the simulated SAR data and the results are evaluated. One method is based on an optimisation based formulation of the sensor fusion problem, leading to batch processing, while the other method is based on the sequential processing of the radar data, leading to a filtering approach. The obtained results are promising for both methods and the obtained performance is comparable with the performance of a high precision navigation aid, such as Global Positioning System (GPS).

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2011. , 80 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1464
National Category
Signal Processing
URN: urn:nbn:se:liu:diva-64056ISBN: 978-91-7393-253-0OAI: diva2:385959
2011-01-21, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (Swedish)
Available from: 2011-02-03 Created: 2011-01-11 Last updated: 2011-02-03Bibliographically approved

Open Access in DiVA

Navigation and SAR Auto-focusing in a Sensor Fusion Framework(1851 kB)1108 downloads
File information
File name FULLTEXT01.pdfFile size 1851 kBChecksum SHA-512
Type fulltextMimetype application/pdf
cover(59 kB)31 downloads
File information
File name COVER01.pdfFile size 59 kBChecksum SHA-512
Type coverMimetype application/pdf

Search in DiVA

By author/editor
Sjanic, Zoran
By organisation
Automatic ControlThe Institute of Technology
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 1108 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 199 hits
ReferencesLink to record
Permanent link

Direct link