Exploiting Synthetic Aperture Radar Signal Processing to Reveal Concealed Building Features and Phenomena
| dc.contributor.author | Corbett, Brandon | |
| dc.date.accessioned | 2024-05-05T11:13:10Z | |
| dc.date.available | 2024-05-05T11:13:10Z | |
| dc.date.issued | 2018-11-15 13:15 | |
| dc.description.abstract | 3MT presented at the 2018 Defence and Security Doctoral Symposium.There has been an increased research interest in the techniques needed to exploit accurate remotely sensed data of the activities within buildings, closed/sealed areas, underground bunkers, etc. One example area which could be influenced by such research includes the detection of illegal or nefarious activities. Low frequency synthetic aperture radar (LF-SAR) can provide one such solution to this remote sensing problem. It has been shown that LF-SAR can be used to generate images of objects located behind a variety of mediums, including within buildings. However, the current literature shows that obtaining a clear picture of the structure and contents of buildings is difficult. It is well known that SAR imagery can be affected by various physical phenomena, which can produce a range of artefacts within the images. These artefacts can lead to confusion and difficulty in analysis, as they can be mistaken for targets. A vibrating scatterer is one such example, as it produces a paired echo signature in the SAR image. On the other hand, these phenomena are of particular interest for the detection of running machinery within a building. It has been shown that a vibrating scatterer can represent aspects of a running machine, e.g. a generator or fan. Therefore understanding the effects produced within a SAR image from a vibrating object behind a wall, could lead to the ability to identify and recognise running machinery within a building from a stand-off location. The intention of this research is to investigate these phenomena and the techniques required for imaging the interiors of buildings and to develop the necessary SAR tools and analysis methods required for extracting crucial intelligence information from this data. | |
| dc.description.sponsorship | Dstl | |
| dc.identifier.citation | Corbett, Brandon (2018). Exploiting Synthetic Aperture Radar Signal Processing to Reveal Concealed Building Features and Phenomena. Cranfield Online Research Data (CORD). Presentation. https://doi.org/10.17862/cranfield.rd.7346609.v1 | |
| dc.identifier.doi | 10.17862/cranfield.rd.7346609.v1 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/21486 | |
| dc.publisher | Cranfield University | |
| dc.rights | CC BY 4.0 | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | 'Airborne SAR' | |
| dc.subject | 'Low-frequency' | |
| dc.subject | 'Data dome' | |
| dc.subject | 'DSDS18 3MT' | |
| dc.subject | 'DSDS18' | |
| dc.subject | 'Photogrammetry and Remote Sensing' | |
| dc.subject | 'Image Processing' | |
| dc.title | Exploiting Synthetic Aperture Radar Signal Processing to Reveal Concealed Building Features and Phenomena | |
| dc.type | Presentation |
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