Dantzig selector based compressive sensing for Radar image enhancement

Shikhar Mann*, Rohan Phogat, Amit Kumar Mishra

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

3 Citations (SciVal)

Abstract

Compressive sensing (CS) is the technique for acquiring and reconstructing a signal utilizing the apriori knowledge that it is sparse in a certain domain. This paper investigates the application of this technique to radar imaging. Present radar systems operate on high bandwidths and demands high sample rates following the Nyquist-Shannon theorem. Compressive Sensing can prove to be a good alternative to reduce data handling, complexity, weight, power demands and costs of the existing radar systems. There are two major novelties in this work. First of all we have used Dantzig selector based CS which gives better result when applied on radar images than that using the conventional l1-norm based CS. Secondly, we also show that Dantzig selector based CS supresses speckle noise in radar images. We demonstrate the results on both simulated and real radar images.

Original languageEnglish
Title of host publicationProceedings of the 2010 Annual IEEE India Conference
Subtitle of host publicationGreen Energy, Computing and Communication, INDICON 2010
PublisherIEEE Press
ISBN (Electronic)978-1-4244-9074-5
ISBN (Print)978-1-4244-9072-1
DOIs
Publication statusPublished - 17 Dec 2010
Externally publishedYes
Event2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010 - Kolkata, India
Duration: 17 Dec 201019 Dec 2010

Publication series

NameProceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010

Conference

Conference2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010
Country/TerritoryIndia
CityKolkata
Period17 Dec 201019 Dec 2010

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