Target Classification in Perimeter Protection with a Micro-Doppler Radar
2016 (English)In: 2016 17TH INTERNATIONAL RADAR SYMPOSIUM (IRS), 2016Conference paper (Refereed)
In security surveillance at the perimeter of critical infrastructure, such as airports and power plants, approaching objects have to be detected and classified. Especially important is to distinguish between humans, animals and vehicles. In this paper, micro-Doppler data (from movement of internal parts of the target) have been collected with a small radar of a low complexity and cost-effective type. From time-velocity diagrams of the data, some physical features have been extracted and used in a support vector machine classifier to distinguish between the classes "human", "animal" and "man-made object". Both the type of radar and the classes are suitable for perimeter protection. The classification result are rather good, 77% correct classification. Particularly interesting is the surprisingly good ability to distinguish between humans and animals. This also indicates that we can choose to have limitations in the radar and still solve the classification task.
Place, publisher, year, edition, pages
International Radar Symposium Proceedings, ISSN 2155-5745
Communication Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:bth-13059ISI: 000381801100095ISBN: 978-1-5090-2518-3OAI: oai:DiVA.org:bth-13059DiVA: diva2:1001797
17th International Radar Symposium (IRS), MAY 10-12, 2016, Krakow, POLAND