Battlefield surveillance is a common application of synthetic aperture radar (SAR), in which minefield detection is a challenging task. In this paper, a novel minefield detection approach is proposed via the morphological diversities between targets and background. Firstly, SAR image speckle is suppressed effectively by total variation, and targets edges are preserved well. Secondly, a nonlinear transform is introduced to map the special distributed targets, e.g. landmines, into spot targets. Lastly, the modification of morphological component analysis is adopted to improve the signal-to-clutter ratio and separate the spot targets from image. The performance of the proposed approach is validated by using the data acquired over an airship mounted SAR system.
2. Jin, T., J. Lou, and Z. M. Zhou, "Extraction of landmine features using a forward-looking ground penetrating radar with MIMO array," IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, No. 10, 4135-4144, 2012.
3. Moussally, G., R. Fries, and R. Bortins, "Ground-penetrating synthetic-aperture radar for wide-area airborne minefield detection," Proc. of SPIE, 1042-1052, 2004.
4. Wang, Y. M., Q. Song, T. Jin, Y. Shi, and X.-T. Huang, "Sparse time-frequency representation based feature extraction method for landmine discrimination," Progress In Electromagnetics Research, Vol. 133, 459-475, 2013.
5. Habib, M. A., et al., "Ca-CFAR detection performance of radar targets embedded in `non centered Chi-2 Gamma' clutter," Progress In Electromagnetics Research, Vol. 88, 135-148, 2008.
6. Kwon, H. and N. M. Nasrabadi, "Kernel RX-algorithm: A nonlinear anomaly detector for hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, No. 2, 388-397, 2005.
7. Chen, J., J. Gao, Y. Zhu, W. Yang, and P. Wang, "A novel image formation algorithm for high-resolution wide-swath spaceborne SAR using compressed sensing on azimuth displacement phase center antenna," Progress In Electromagnetics Research, Vol. 125, 527-543, 2012.
8. Starck, J.-L., M. Elad, and D. Donoho, "Image decomposition via the combination of sparse representation and a variational approach," IEEE Transactions on Image Processing, Vol. 14, No. 10, 1570-1582, 2005.
9. Bobin, J., et al., "Sparsity and morphological diversity in blind source separation," IEEE Transactions on Image Processing, Vol. 16, No. 11, 2662-2674, 2007.
10. Huang, C.-W. and K.-C. Lee, "Application of ICA technique to PCA based radar target recognition," Progress In Electromagnetics Research, Vol. 105, 157-170, 2010.
11. Candes, E. J., et al., "Fast discrete curvelet transforms," Applied and Computational Mathematics, Vol. 91125, 1-43, Caltech, Pasadena, CA, 2005.
12. Ahmed, N., T. Natarajan, and K. R. Rao, "Discrete cosine transform," IEEE Transactions on Computers, 90-93, 1974.
13. Kaplan, L. M., "Improved SAR target detection via extended fractal features," IEEE Transactions on Aerospace and Electronic Systems, Vol. 37, No. 2, 436-451, 2001.
14. Kaplan, L. M., R. Murenzi, and K. Namuduri, "Extended fractal feature for first stage SAR target detection," Proc. of SPIE, Vol. 3721, 35-46, 1999.
15. Rudin, L. I., S. Osher, and E. Fatemi, "Nonlinear total variation based noise removal algorithms," Physica D: Nonlinear Phenomena, Vol. 60, 259-268, 1992.
16. Chan, T. F. and S. Esedoglu, "Aspects of total variation regularized L1 function approximation," UCLA CAM Report, 04-07, 2004.
17. Lee, J. S., "Digital image enhancement and noise filtering by use of local statistics," IEEE Transactions on Pattern Analysis Machine Intelligence, 165-168, 1980.
18. Kuan, D. T., et al., "Adaptive noise smoothing filter for images with signal-dependent noise," IEEE Transactions on Pattern Analysis Machine Intelligence, 165-177, 1985.
19. Cheng, J., G. Gao, W. Ding, X. Ku, and J. Sun, "An improved scheme for parameter estimation of G0 distribution model in high-resolution SAR images," Progress In Electromagnetics Research, Vol. 134, 23-46, 2013.
20. Song, Q., et al., Results from an airship-mounted ultra-wideband synthetic aperture radar for penetrating surveillance, Asia-Pacific Conference on Synthetic Aperture Radar, 194-197, Seoul, Korea, 2011.
21. Wei, S.-J., X.-L. Zhang, J. Shi, and G. Xiang, "Sparse reconstruction for SAR imaging based on compressed sensing," Progress In Electromagnetics Research, Vol. 109, 63-81, 2010.
22. Candes, E. J., J. Romberg, and T. Tao, "Robust uncertainty principles: Extract signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, Vol. 52, 489-509, 2006.
23. Makal, S., A. Kizilay, and L. Durak, "On the target classification through wavelet-compressed scattered ultrawide-band electric field data and ROC analysis," Progress In Electromagnetics Research, Vol. 82, 419-431, 2008.