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Sparsity-based multipath exploitatio...

Leigsnering, Michael.

Sparsity-based multipath exploitation for through-the-wall radar imaging

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Sparsity-based multipath exploitation for through-the-wall radar imagingby Michael Leigsnering.
作者:	Leigsnering, Michael.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xx, 108 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Compressed sensing (Telecommunication)
電子資源:	http://dx.doi.org/10.1007/978-3-319-74283-0
ISBN:	9783319742830$q(electronic bk.)

Sparsity-based multipath exploitation for through-the-wall radar imaging
Leigsnering, Michael.

Sparsity-based multipath exploitation for through-the-wall radar imaging[electronic resource] /by Michael Leigsnering. - Cham :Springer International Publishing :2018. - xx, 108 p. :ill. (some col.), digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

This thesis reports on sparsity-based multipath exploitation methods for through-the-wall radar imaging. Multipath creates ambiguities in the measurements provoking unwanted ghost targets in the image. This book describes sparse reconstruction methods that are not only suppressing the ghost targets, but using multipath to one's advantage. With adopting the compressive sensing principle, fewer measurements are required for image reconstruction as compared to conventional techniques. The book describes the development of a comprehensive signal model and some associated reconstruction methods that can deal with many relevant scenarios, such as clutter from building structures, secondary reflections from interior walls, as well as stationary and moving targets, in urban radar imaging. The described methods are evaluated here using simulated as well as measured data from semi-controlled laboratory experiments.

ISBN: 9783319742830$q(electronic bk.)

Standard No.: 10.1007/978-3-319-74283-0doiSubjects--Topical Terms:

769143
Compressed sensing (Telecommunication)

LC Class. No.: TK5102.9

Dewey Class. No.: 621.3822

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