OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 20, Iss. 1 — Jan. 1, 2003
  • pp: 32–39

Statistical–physical model for foliage clutter in ultra-wideband synthetic aperture radar images

Amit Banerjee and Rama Chellappa  »View Author Affiliations

JOSA A, Vol. 20, Issue 1, pp. 32-39 (2003)

View Full Text Article

Enhanced HTML    Acrobat PDF (290 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Analyzing foliage-penetrating (FOPEN) ultra-wideband synthetic aperture radar (SAR) images is a challenging problem owing to the noisy and impulsive nature of foliage clutter. Indeed, many target-detection algorithms for FOPEN SAR data are characterized by high false-alarm rates. In this work, a statistical–physical model for foliage clutter is proposed that explains the presence of outliers in the data and suggests the use of symmetric alpha-stable (SαS) distributions for accurate clutter modeling. Furthermore, with the use of general assumptions of the noise sources and propagation conditions, the proposed model relates the parameters of the SαS model to physical parameters such as the attenuation coefficient and foliage density.

© 2003 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(280.0280) Remote sensing and sensors : Remote sensing and sensors

Original Manuscript: May 20, 2001
Revised Manuscript: June 27, 2002
Manuscript Accepted: June 28, 2002
Published: January 1, 2003

Amit Banerjee and Rama Chellappa, "Statistical–physical model for foliage clutter in ultra-wideband synthetic aperture radar images," J. Opt. Soc. Am. A 20, 32-39 (2003)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. M. Ressler, L. Happ, L. Nguyen, T. Ton, M. Bennett, “The Army Research Laboratory ultra-wideband testbed radars,” in Proceedings of the IEEE International Radar Conference (Institute of Electrical and Electronics Engineers, New York, 1995), pp. 686–691.
  2. R. O. Harger, “Harmonic radar systems for near-ground in-foliage non-linear scatterers,” IEEE Trans. Aerosp. Electron. Syst. AES-12, 230–245 (1976). [CrossRef]
  3. J. G. Fleischman, S. Ayasli, E. M. Adams, D. R. Gosselin, “Foliage penetration experiment: part I: foliage attenuation and backscatter analysis of SAR imagery,” IEEE Trans. Aerosp. Electron. Syst. 32, 134–144 (1996). [CrossRef]
  4. J. W. McCorkle, “Early results from the ARL UWB foliage penetration SAR,” in Underground and Obscured-Object Imaging and Detection, N. K. Del Grande, I. Cindrich, P. B. Johnson, eds., Proc. SPIE1942, 88–95 (1993). [CrossRef]
  5. E. Jakeman, P. N. Pusey, “A model for non-Rayleigh sea echo,” IEEE Trans. Antennas Propag. 24, 806–814 (1976). [CrossRef]
  6. K. J. Sangston, K. R. Gerlach, “Coherent detection of radar targets in non-Gaussian background,” IEEE Trans. Aerosp. Electron. Syst. AES-30, 330–340 (1978).
  7. E. Conte, M. Longo, “Characterization of radar clutter as spherically-invariant random processes,” Proc. IEEE 134, 191–197 (1987).
  8. S. Bochner, “Stable law of probability and completely monotone functions,” Duke Math. J. 3, 726–728 (1937). [CrossRef]
  9. J. Ilow, D. Hatzinakos, “Analytic alpha-stable noise modeling in a Poisson field of interferers or scatterers,” IEEE Trans. Signal Process. 46, 1601–1611 (1998). [CrossRef]
  10. R. Kapoor, A. Banerjee, G. A. Tsihrintzis, N. Nandhakumar, “Detection of targets in heavy-tailed foliage clutter using an ultra-wideband (UWB) radar and alpha-stable clutter models,” IEEE Trans. Aerosp. Electron. Syst. 35, 819–834 (1999). [CrossRef]
  11. A. Banerjee, P. Burlina, R. Chellappa, “Adaptive target detection in foliage-penetrating SAR images using alpha-stable models,” IEEE Trans. Image Process. 13, 1823–1831 (1999). [CrossRef]
  12. W. Feller, An Introduction to Probability Theory and Its Applications, (Wiley, New York, 1971), Vol. 2.
  13. U. A. Muller, M. M. Dacorogna, O. V. Pictet, “Heavy tails in high-frequency financial data,” in A Practical Guide to Heavy Tails, R. J. Adler, R. Feldman, M. Taqqu, eds. (Birkhauser, Boston, Mass., 1998), pp. 55–78.
  14. E. F. Fama, R. Roll, “Parameter estimates for symmetric stable distributions,” J. Am. Stat. Assoc. 66, 331–338 (1971). [CrossRef]
  15. J. H. McCulloch, “Financial applications of stable distributions,” in Statistical Methods in Finance, Handbook of Statistics (North-Holland, New York, 1996), Vol. 14, pp. 383–425.
  16. B. W. Stuck, B. Kleiner, “A statistical analysis of telephone noise,” Bell Syst. Tech. J. 53, 1263–1320 (1974). [CrossRef]
  17. V. M. Zolotarev, One-Dimensional Stable Distributions (American Mathematical Society, Providence, R.I., 1996).
  18. C. L. Nikias, M. Shao, Signal Processing with Alpha-Stable Distributions and Applications (Wiley, New York, 1995).
  19. G. A. Tsihrintzis, C. L. Nikias, “Incoherent receivers in alpha-stable impulsive noise,” IEEE Trans. Signal Process. 43, 2225–2229 (1995). [CrossRef]
  20. G. Samorodnitsky, M. Taqqu, Stable Non-Gaussian Random Processes (Chapman & Hall, New York, 1994).
  21. J. P. Nolan, “Numerical computation of stable densities and distribution function,” Commun. Stat. Stochastic Models 133, 759–774 (1997).
  22. D. Middleton, “Non-Gaussian noise models in signal processing for telecommunications: new methods and results for class A and class B noise models,” IEEE Trans. Inf. Theory 45, 1129–1149 (1999). [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.


Fig. 1 Fig. 2 Fig. 3
Fig. 4

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited