Skip to main content
Log in

A MoLC+MoM-based G0 distribution parameter estimation method with application to synthetic aperture radar target detection

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate (CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar (SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant (MoLC) + method of moment (MoM)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new MoLC+MoM-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. LI Yu, WANG Shi-xi, JI Ke-feng, SU Yi. A new method of automatic target discrimination in high-resolution SAR image [J]. Journal of Nat Univ of Defense Technol, 2007, 29(3): 81–84.

    Google Scholar 

  2. KULTIKKAD S, CHELLAPPA R. Non-Gaussian CFAR techniques for target detection in high resolution SAR images [C]// Int Conf in Image Processing. Washington, DC: IEEE, 1995: 910–914.

    Google Scholar 

  3. SALAZAR J S, HUSH D R. Statistical modeling of target and clutter in single-look non-polarimetric SAR imagery [C]// Proceedings of IASTED Int Conf on Signal and Image Processing. 1998: 272–276.

    Google Scholar 

  4. FRERY A C, MULLER H J, YANASSE C F, SANT’ ANNA S. A model for extremely heterogeneous clutter [J]. IEEE Trans on Geosci Remote Sens, 1997, 35(3): 648–659.

    Article  Google Scholar 

  5. FREITAS C C, FRERY A C, CORREIA A H. The polari metric G distribution for SAR data analysis [J]. Environmetries, 2005, 16(1): 13–31.

    Article  MathSciNet  Google Scholar 

  6. ELTOFT T. Modeling the amplitude statistics of ultrasonic images [J]. IEEE Trans on Medical Imaging, 2006, 25(2): 229–240.

    Article  Google Scholar 

  7. GRECO M S, GINI F. Statistical analysis of high-resolution SAR ground clutter data [J]. IEEE Trans on Geosci Remote Sens, 2007, 45(3): 566–575.

    Article  Google Scholar 

  8. SILVA M, CRIBARI-NETO F, FRERY A C. Improved likelihood inference for the roughness parameter of the GA0 distribution [J]. Environmetrics, 2008, 19(4): 347–368.

    Article  MathSciNet  Google Scholar 

  9. ZHU Zheng-wei. Shipborne radar maneuvering target tracking based on the variable structure adaptive grid interacting multiple model [J]. Journal of Zhejiang University: Sci C, 2013, 14(9): 733–742.

    Article  Google Scholar 

  10. DCVORE M D, O’SULLIVAN J A. Statistical assemmment of model fit for synthetic aperture radar data [J]. SPIE, 2001, 4382: 379–388.

    Google Scholar 

  11. GAO Gui, LIU Li, ZHAO Ling-jun, SHI Gong-tao, KUANG Gang-yao. An adaptive and fast CFAR algorithm based on automatic censoring for target detection in high-resolution SAR images [J]. IEEE Trans on Geosci Remote Sens, 2009, 47(6): 1685–1697.

    Article  Google Scholar 

  12. NOVAK L M, HESSE S R. On the performance of order-statistics CFAR detectors [C]// IEEE 25th Asilomar Conf Signals, Syst, Comput Pacific Grove. CA: IEEE, 1991: 835–840.

    Google Scholar 

  13. GIERULL C H, SIKANETA I C. Estimating the effective number of looks in interferometric SAR data [J]. IEEE Trans on Geosci Remote Sens, 2002, 40(8): 1733–1742.

    Article  Google Scholar 

  14. ABDELFATTAH R, NICOLAS J M. Interferometric SAR coherence magnitude estimation using second kind statistics [J]. IEEE Trans on Geosci Remote Sens, 2006, 44(7): 1942–1953.

    Article  Google Scholar 

  15. LI Wu-zhou, KU Xi-shu, CHENG Jiang-hua, WANG Jin-chao. A new G0 distribution parameter estimation method for SAR images [C]// The 11th National Radar Academic Conference. Beijing: NRAC, 2010: 210–214.

    Google Scholar 

  16. TISON C, NICOLAS J M, TUPIN F, MAITRE H. A new statistical model for Markovian classification of urban areas in high-resolution SAR images [J]. IEEE Trans on Geosci Remote Sens, 2004, 42(10): 2046–2057.

    Article  Google Scholar 

  17. ANFINSEN S, ELTOFT T. Application of the matrix-variate Mellin transform to analysis of polarimetric radar images [J]. IEEE Trans on Geosci Remote Sens, 2011, 49(6): 2281–2295.

    Article  Google Scholar 

  18. WANG Lian-xiang, FANG De-zhi, ZHANG Min-yong. Handbook of mathematics [M]. Beijing: Higher Education Press, 2005: 352–354. (in Chinese)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zheng-wei Zhu  (朱正为).

Additional information

Foundation item: Project(61105020) supported by the National Natural Science Foundation of China; Project(13zxtk08) supported by the Key Research Platform for Research Projects of Southwest University of Science and Technology, China

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, Zw., Zhou, Jj. & Guo, Yy. A MoLC+MoM-based G0 distribution parameter estimation method with application to synthetic aperture radar target detection. J. Cent. South Univ. 22, 2207–2217 (2015). https://doi.org/10.1007/s11771-015-2745-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-015-2745-x

Keywords

Navigation