OSA's Digital Library

Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 11 — Jun. 2, 2014
  • pp: 13515–13530

Adaptive millimeter-wave synthetic aperture imaging for compressive sampling of sparse scenes

Alex Mrozack, Martin Heimbeck, Daniel L. Marks, Jonathan Richard, Henry O. Everitt, and David J. Brady  »View Author Affiliations

Optics Express, Vol. 22, Issue 11, pp. 13515-13530 (2014)

View Full Text Article

Enhanced HTML    Acrobat PDF (4454 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



We apply adaptive sensing techniques to the problem of locating sparse metallic scatterers using high-resolution, frequency modulated continuous wave W-band RADAR. Using a single detector, a frequency stepped source, and a lateral translation stage, inverse synthetic aperture RADAR reconstruction techniques are used to search for one or two wire scatterers within a specified range, while an adaptive algorithm determined successive sampling locations. The two-dimensional location of each scatterer is thereby identified with sub-wavelength accuracy in as few as 1/4 the number of lateral steps required for a simple raster scan. The implications of applying this approach to more complex scattering geometries are explored in light of the various assumptions made.

© 2014 Optical Society of America

OCIS Codes
(120.4290) Instrumentation, measurement, and metrology : Nondestructive testing
(110.1085) Imaging systems : Adaptive imaging
(120.1088) Instrumentation, measurement, and metrology : Adaptive interferometry
(110.1758) Imaging systems : Computational imaging

ToC Category:
Imaging Systems

Original Manuscript: January 23, 2014
Revised Manuscript: April 21, 2014
Manuscript Accepted: May 8, 2014
Published: May 28, 2014

Alex Mrozack, Martin Heimbeck, Daniel L. Marks, Jonathan Richard, Henry O. Everitt, and David J. Brady, "Adaptive millimeter-wave synthetic aperture imaging for compressive sampling of sparse scenes," Opt. Express 22, 13515-13530 (2014)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. M. S. Heimbeck, D. L. Marks, D. Brady, H. O. Everitt, “Terahertz interferometric synthetic aperture tomography for confocal imaging systems,” Opt. Lett. 37, 1316–1318 (2012). [CrossRef] [PubMed]
  2. T. S. Ralston, D. L. Marks, P. S. Carney, S. A. Boppart, “Inverse scattering for optical coherence tomography,” J. Opt. Soc. Am. A 23, 1027–1037 (2006). [CrossRef]
  3. L. Li, W. Zhang, F. Li, “Derivation and discussion of the sar migration algorithm within inverse scattering problem: Theoretical analysis,” Geoscience and Remote Sensing, IEEE Transactions on 48, 415–422 (2010). [CrossRef]
  4. P. Potuluri, M. Gehm, M. Sullivan, D. Brady, “Measurement-efficient optical wavemeters,” Opt. Express 12, 6219–6229 (2004). [CrossRef] [PubMed]
  5. E. Candes, “The restricted isometry property and its implications for compressed sensing,” Comptes Rendus Mathematique 346, 589–592 (2008). [CrossRef]
  6. D. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006). [CrossRef]
  7. E. Candes, M. Wakin, “An introduction to compressive sampling,” IEEE Sig. Proc. Mag. 25, 21–30 (2008). [CrossRef]
  8. W. L. Chan, M. L. Moravec, R. G. Baraniuk, D. M. Mittleman, “Terahertz imaging with compressed sensing and phase retrieval,” Opt. Lett. 33, 974–976 (2008). [CrossRef] [PubMed]
  9. D. J. Brady, K. Choi, D. L. Marks, R. Horisaki, S. Lim, “Compressive holography,” Opt. Express 17, 13040–13049 (2009). [CrossRef] [PubMed]
  10. C. F. Cull, D. A. Wikner, J. N. Mait, M. Mattheiss, D. J. Brady, “Millimeter-wave compressive holography,” Appl. Opt. 49, E67–E82 (2010). [CrossRef] [PubMed]
  11. E. Lebed, P. J. Mackenzie, M. V. Sarunic, F. M. Beg, “Rapid volumetric oct image acquisition using compressive sampling,” Opt. Express 18, 21003–21012 (2010). [CrossRef] [PubMed]
  12. E. Candes, T. Tao, “Near-optimal signal recovery from random projections: Universal encoding strategies?” IEEE Trans. Inf. Theory 52, 5406–5425 (2006). [CrossRef]
  13. M. Duarte, Y. Eldar, “Structured compressed sensing: From theory to applications,” IEEE Trans. Sig. Proc. 59, 4053–4085 (2011). [CrossRef]
  14. W. U. Bajwa, R. Calderbank, S. Jafarpour, “Why gabor frames? two fundamental measures of coherence and their role in model selection,” J. Commun. Netw. 12, 289–307 (2010). [CrossRef]
  15. J. Duarte-Carvajalino, G. Sapiro, “Learning to sense sparse signals: Simultaneous sensing matrix and sparsifying dictionary optimization,” IEEE Trans. Image Process. 18, 1395–1408 (2009). [CrossRef] [PubMed]
  16. Z. Zhang, T. Buma, “Adaptive terahertz imaging using a virtual transceiver and coherence weighting,” Opt. Express 17, 17812–17817 (2009). [CrossRef] [PubMed]
  17. K. Kim, D.-G. Lee, W.-G. Ham, J. Ku, S.-H. Lee, C.-B. Ahn, J.-H. Son, H. Park, “Adaptive compressed sensing for the fast terahertz reflection tomography,” IEEE trans. Terahertz Sci. Technol. 3, 395–401 (2013). [CrossRef]
  18. D. J. MacKay, “Information-based objective functions for active data selection,” Neural Computation 4, 590–604 (1992). [CrossRef]
  19. Y. Zhang, X. Liao, L. Carin, “Detection of buried targets via active selection of labeled data: application to sensing subsurface uxo,” IEEE Trans. Geosci. Remote Sensing 42, 2535–2543 (2004). [CrossRef]
  20. G. Tang, B. Bhaskar, P. Shah, B. Recht, “Compressive sensing off the grid,” in “Communication, Control, and Computing (Allerton), 2012 50th Annual Allerton Conference on,” (2012), pp. 778–785.
  21. D. J. Brady, Optical Imaging and Spectroscopy (Wiley-interscience, New Jersey, USA, 2008).
  22. M. E. Tipping, “Sparse bayesian learning and the relevance vector machine,” J. Mach. Learn. Res. 1, 211–244 (2001).
  23. S. Ji, Y. Xue, L. Carin, “Bayesian compressive sensing,” IEEE Trans. Sig. Process. 56, 2346–2356 (2008). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited