Dantzig selector based compressive sensing for Radar image enhancement

Shikhar Mann; Rohan Phogat; Amit Kumar Mishra

doi:10.1109/INDCON.2010.5712730

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 proceeding › Conference Proceeding (Non-Journal item)

3 Citations (Scopus)

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 language	English
Title of host publication	Proceedings of the 2010 Annual IEEE India Conference
Subtitle of host publication	Green Energy, Computing and Communication, INDICON 2010
Publisher	IEEE Press
ISBN (Electronic)	978-1-4244-9074-5
ISBN (Print)	978-1-4244-9072-1
DOIs	https://doi.org/10.1109/INDCON.2010.5712730
Publication status	Published - 17 Dec 2010
Externally published	Yes
Event	2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010 - Kolkata, India Duration: 17 Dec 2010 → 19 Dec 2010

Publication series

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

Conference

Conference	2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010
Country/Territory	India
City	Kolkata
Period	17 Dec 2010 → 19 Dec 2010

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/INDCON.2010.5712730

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Mann, S., Phogat, R., & Mishra, A. K. (2010). Dantzig selector based compressive sensing for Radar image enhancement. In Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010 Article 5712730 (Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010). IEEE Press. https://doi.org/10.1109/INDCON.2010.5712730

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title = "Dantzig selector based compressive sensing for Radar image enhancement",

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.",

author = "Shikhar Mann and Rohan Phogat and Mishra, {Amit Kumar}",

year = "2010",

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booktitle = "Proceedings of the 2010 Annual IEEE India Conference",

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note = "2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010 ; Conference date: 17-12-2010 Through 19-12-2010",

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Mann, S, Phogat, R & Mishra, AK 2010, Dantzig selector based compressive sensing for Radar image enhancement. in Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010., 5712730, Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010, IEEE Press, 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010, Kolkata, India, 17 Dec 2010. https://doi.org/10.1109/INDCON.2010.5712730

Dantzig selector based compressive sensing for Radar image enhancement. / Mann, Shikhar; Phogat, Rohan; Mishra, Amit Kumar.
Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010. IEEE Press, 2010. 5712730 (Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010).

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

TY - GEN

T1 - Dantzig selector based compressive sensing for Radar image enhancement

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AU - Phogat, Rohan

AU - Mishra, Amit Kumar

PY - 2010/12/17

Y1 - 2010/12/17

N2 - 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.

AB - 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.

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SN - 978-1-4244-9072-1

T3 - Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010

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Mann S, Phogat R, Mishra AK. Dantzig selector based compressive sensing for Radar image enhancement. In Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010. IEEE Press. 2010. 5712730. (Proceedings of the 2010 Annual IEEE India Conference: Green Energy, Computing and Communication, INDICON 2010). doi: 10.1109/INDCON.2010.5712730

Dantzig selector based compressive sensing for Radar image enhancement

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