Vol. 119
Latest Volume
All Volumes
PIER 180 [2024] PIER 179 [2024] PIER 178 [2023] PIER 177 [2023] PIER 176 [2023] PIER 175 [2022] PIER 174 [2022] PIER 173 [2022] PIER 172 [2021] PIER 171 [2021] PIER 170 [2021] PIER 169 [2020] PIER 168 [2020] PIER 167 [2020] PIER 166 [2019] PIER 165 [2019] PIER 164 [2019] PIER 163 [2018] PIER 162 [2018] PIER 161 [2018] PIER 160 [2017] PIER 159 [2017] PIER 158 [2017] PIER 157 [2016] PIER 156 [2016] PIER 155 [2016] PIER 154 [2015] PIER 153 [2015] PIER 152 [2015] PIER 151 [2015] PIER 150 [2015] PIER 149 [2014] PIER 148 [2014] PIER 147 [2014] PIER 146 [2014] PIER 145 [2014] PIER 144 [2014] PIER 143 [2013] PIER 142 [2013] PIER 141 [2013] PIER 140 [2013] PIER 139 [2013] PIER 138 [2013] PIER 137 [2013] PIER 136 [2013] PIER 135 [2013] PIER 134 [2013] PIER 133 [2013] PIER 132 [2012] PIER 131 [2012] PIER 130 [2012] PIER 129 [2012] PIER 128 [2012] PIER 127 [2012] PIER 126 [2012] PIER 125 [2012] PIER 124 [2012] PIER 123 [2012] PIER 122 [2012] PIER 121 [2011] PIER 120 [2011] PIER 119 [2011] PIER 118 [2011] PIER 117 [2011] PIER 116 [2011] PIER 115 [2011] PIER 114 [2011] PIER 113 [2011] PIER 112 [2011] PIER 111 [2011] PIER 110 [2010] PIER 109 [2010] PIER 108 [2010] PIER 107 [2010] PIER 106 [2010] PIER 105 [2010] PIER 104 [2010] PIER 103 [2010] PIER 102 [2010] PIER 101 [2010] PIER 100 [2010] PIER 99 [2009] PIER 98 [2009] PIER 97 [2009] PIER 96 [2009] PIER 95 [2009] PIER 94 [2009] PIER 93 [2009] PIER 92 [2009] PIER 91 [2009] PIER 90 [2009] PIER 89 [2009] PIER 88 [2008] PIER 87 [2008] PIER 86 [2008] PIER 85 [2008] PIER 84 [2008] PIER 83 [2008] PIER 82 [2008] PIER 81 [2008] PIER 80 [2008] PIER 79 [2008] PIER 78 [2008] PIER 77 [2007] PIER 76 [2007] PIER 75 [2007] PIER 74 [2007] PIER 73 [2007] PIER 72 [2007] PIER 71 [2007] PIER 70 [2007] PIER 69 [2007] PIER 68 [2007] PIER 67 [2007] PIER 66 [2006] PIER 65 [2006] PIER 64 [2006] PIER 63 [2006] PIER 62 [2006] PIER 61 [2006] PIER 60 [2006] PIER 59 [2006] PIER 58 [2006] PIER 57 [2006] PIER 56 [2006] PIER 55 [2005] PIER 54 [2005] PIER 53 [2005] PIER 52 [2005] PIER 51 [2005] PIER 50 [2005] PIER 49 [2004] PIER 48 [2004] PIER 47 [2004] PIER 46 [2004] PIER 45 [2004] PIER 44 [2004] PIER 43 [2003] PIER 42 [2003] PIER 41 [2003] PIER 40 [2003] PIER 39 [2003] PIER 38 [2002] PIER 37 [2002] PIER 36 [2002] PIER 35 [2002] PIER 34 [2001] PIER 33 [2001] PIER 32 [2001] PIER 31 [2001] PIER 30 [2001] PIER 29 [2000] PIER 28 [2000] PIER 27 [2000] PIER 26 [2000] PIER 25 [2000] PIER 24 [1999] PIER 23 [1999] PIER 22 [1999] PIER 21 [1999] PIER 20 [1998] PIER 19 [1998] PIER 18 [1998] PIER 17 [1997] PIER 16 [1997] PIER 15 [1997] PIER 14 [1996] PIER 13 [1996] PIER 12 [1996] PIER 11 [1995] PIER 10 [1995] PIER 09 [1994] PIER 08 [1994] PIER 07 [1993] PIER 06 [1992] PIER 05 [1991] PIER 04 [1991] PIER 03 [1990] PIER 02 [1990] PIER 01 [1989]
2011-07-19
SAR Image Simulation with Application to Target Recognition
By
Progress In Electromagnetics Research, Vol. 119, 35-57, 2011
Abstract
This paper presents a novel synthetic aperture radar (SAR) image simulation approach to target recognition, which consists of two frameworks, referred to as the satellite SAR images simulation and the target recognition and identification. The images simulation makes use of the sensor and target geo-location relative to the Earth, movement of SAR sensor, SAR system parameters, radiometric and geometric characteristics of the target, and target radar cross section (RCS), orbital parameters estimation, SAR echo signal generation and image focusing to build SAR image database. A hybrid algorithm that combines the physical optics, physical diffraction theory, and shooting and bouncing rays was used to compute the RCS of complex radar targets. Such database is vital for aided target recognition and identification system Followed by reformulating the projection kernel in an optimization equation form, the target's reflectivity field can be accurately estimated. Accordingly, the target's features can be effectively enhanced and extracted, and the dominant scattering centers are well separated. Experimental results demonstrate that the simulated database developed in this paper is well suited for target recognition. Performance is extensively tested and evaluated from real images by Radarsat-2 and TerraSAR-X. Effectiveness and efficiency of the proposed method are further confirmed.
Citation
Yang-Lang Chang, Cheng-Yen Chiang, and Kunshan Chen, "SAR Image Simulation with Application to Target Recognition," Progress In Electromagnetics Research, Vol. 119, 35-57, 2011.
doi:10.2528/PIER11061507
References

1. Rihaczek, A. W. and S. J. Hershkowitz, Theory and Practice of Radar Target Identification, Artech House, 2000.

2. Huang, C. W. and K. C. Lee, "Frequency-diversity RCS based target recognition with ICA projection," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 17-18, 2547-2559, 2010.

3. Guo, K. Y., Q. Li, and X. Q. Sheng, "A precise recognition method of missile warhead and decoy in multi-target scene," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 5-6, 641-652, 2010.

4. Tian, B., D. Y. Zhu, and Z. D. Zhu, "A novel moving target detection approach for dual-channel SAR system," Progress In Electromagnetics Research, Vol. 115, 191-206, 2011.

5. Wang, X. F., J. F. Chen, Z. G. Shi, and K. S. Chen, "Fuzzy-control-based particle filter for maneuvering target tracking," Progress In Electromagnetics Research, Vol. 118, 1-15, 2011.

6. Lee, J. S. and E. Pottier, Polarimetric Radar Imaging: From Basics to Applications, CRC Press, 2009.

7. Margarit, G., J. J. Mallorqui, J. M. Rius, and J. Sanz-Marcos, "On the usage of GRECOSAR, an orbital polarimetric SAR simulator of complex targets, to vessel classification studies," IEEE Trans. Geoscience and Remote Sens., Vol. 44, 3517-3526, 2006.

8. Lee, J. S., "Digital image enhancement and noise filtering by use of local statistics ," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 2, 165-168, 1980.

9. Chang, Y. L., L. S. Liang, C. C. Han, J. P. Fang, W. Y. Liang, and K. S. Chen, "Multisource data fusion for landslide classification using generalized positive boolean functions," IEEE Trans. Geosci. Remote Sensing, Vol. 45, 1697-1708, 2007.

10. Wang, J. and L. Sun, "Study on ship target detection and recognition in SAR imagery," CISE'09 Proceedings of the 2009 First IEEE International Conference on Information Science and Engineering , 1456-1459, 2009.

11. Çetin, M. and W. C. Karl, "Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization," IEEE Trans. on Image Processing, Vol. 10, 623-631, 2001.

12. Çetin, M., W. C. Karl, and A. S. Willsky, "Feature-preserving regularization method for complex-valued inverse problems with application to coherent imaging," Optical Engineering, Vol. 45, 017003-1-11, 2006.

13. Chiang, C. Y., K. S. Chen, C. T. Wang, and N. S. Chou, "Feature enhancement of stripmap-mode SAR images based on an optimization scheme," IEEE Geoscience and Remote Sensing Letters, Vol. 6, 870-874, 2009.

14. Tzeng, Y., K. S Chen, W. L. Kao, and A. K. Fung, "A dynamic learning neural network for remote sensing applications," IEEE Trans. Geosci. Remote Sensing, Vol. 32, 1096-1102, 1994.

15. Chen, K. S., Y. C. Tzeng, C. F. Chen, and W. L. Kao, "Land-cover classification of multispectral imagery using a dynamic learning neural network," Photogrammet. Eng. Remote Sensing, Vol. 61, 403-408, 1995.

16. Chen, K. S., Y. C. Tzeng, and W. L. Kao, "Retrieval of surface parameters using dynamic learning neural network," International Geoscience and Remote Sensing Symposium 1993, IGARSS '93, Better Understanding of Earth Environment , Vol. 2, 505-507, 1993.

17. Chen, K. S., W. P. Huang, D. W. Tsay, and F. Amar, "Classification of multifrequency polarimetric SAR image using a dynamic learning neural network," IEEE Trans. Geosci. Remote Sensing, Vol. 34, 814-820, 1996.

18. Tzeng, Y. C. and K. S. Chen, "A fuzzy neural network to SAR image classification," IEEE Trans. Geosci. Remote Sensing, Vol. 36, 301-307, 1998.

19. Cumming, I. and F. Wong, Digital Signal Processing of Synthetic Aperture Radar Data: Algorithms and Implementation, Artech House, 2004.

20. Curlander, J. C. and R. N. McDonough, Synthetic Aperture Radar: Systems and Signal Processing, Wiley-Interscience, 1991.

21. Chen, C. C., Y. Cheng, and M. Ouhyoung, "Radar cross section analysis and visualization system," Proceeding of Computer Graphics Workshop 1995, 12-16, Taipei, Taiwan, 1995.

22. Lee, H., R. C. Chou, and S. W. Lee, "Shooting and bouncing rays: Calculating the RCS of an arbitrarily shaped cavity," IEEE Trans. Antennas Propag., Vol. 37, 194-205, 1989.

23. Chen, S. H. and S. K. Jeng, "An SBR/image approach for indoor radio propagation in a corridor," Trans. IEICE Electron., Vol. E78-C, No. 8, 1058-1062, 1995.

24. Lee, J. S., "Re¯ned filtering of image noise using local statistics," Comput., Vis., Graph., Image Process., Vol. 15, 380-389, 1981.

25. Lee, J. S., M. R. Grunes, and R. Kwok, "Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution," Int. J. Remote Sensing, Vol. 15, 2299-2311, 1994.

26. Lee, J. S., P. Dewaele, P. Wambacq, A. Oosterlinck, and I. Jurkevich, "Speckle filtering of synthetic aperture radar images: A review ," Remote Sens. Rev., Vol. 8, 313-340, 1994.

27. Schleher, D. C., "Radar detection in Weibull clutter," IEEE Trans. Aerosu. Electron. Svst., Vol. 12, 736-743, 1976.

28. Boothe, R. R., "The Weibull distribution applied to the ground clutter backscattering coefficient," Automatic Detection and Radar-data Processing, D. C. Schleher (ed.), 435-450, Artech House, 1980.

29. Fung, A. K., Microwave Scattering and Emission Models and Their Applications, Artech House, 1994.

30. Chen, K. S. and A. K. Fung, "Frequency dependence of signal statistics from vegetation components," IEE Processings --- Radar, Sonar and Navigation, Vol. 142, No. 6, 301-305, 1996.

31. Montenbruck, O. and E. Gill, Satellite Orbits: Models, Methods, and Applications, Springer-Verlag, 2000.

32. Vallado, D. A. and W. D. McClain, Fundamentals of Astrody-namics and Applications, 3rd Ed., Microcosm Press, Springer, 2007.

33. Henry, M. F. "NORAD SGP4/SDP4 implementations," Available: http://www. zeptomoby.com/satellites/.

34. Vallado, D., P. Crawford, R. Hujsak, and T. S. Kelso, "Revisiting spacetrack report# 3," AIAA, Vol. 6753, 1-88, 2006.

35. Miura, N. Z., "Comparison and design of simplified general perturbation models," California Polytechnic State University, San Luis Obispo2009, Earth Orientation Centre, Available: http://hpiers.obspm.fr/eop-pc.

36. Cafforio, C., C. Prati, and F. Rocca, "SAR data focusing using seismic migration techniques," IEEE Transactions on Aerospace and Electronic Systems, Vol. 27, 194-207, 1991.

37. Moreira, A., J. Mittermayer, and R. Scheiber, "Extended chirp scaling algorithm for air- and spaceborne SAR data processing in stripmap and ScanSAR imaging modes," IEEE Trans. Geosci. Remote Sensing, Vol. 34, 1123-1136, 1996.

38. Li, F.-K., D. N. Held, J. C. Curlander, and C. Wu, "Doppler parameter estimation for spaceborne synthetic-aperture radars," IEEE Trans. Geosci. Remote Sensing, Vol. 23, 47-56, 1985.

39. Strang, G., "Introduction to Applied Mathematics," Cambridge Press, Wellesley, 1986.

40. Bini, D., Toeplitz Matrices, Algorithms and Applications, ECRIM News Online Edition, No. 22, Jul. 1995.

41. Tzeng, Y. C. and K. S. Chen, "Fractional Brownian motion, fractional noises and applications," Opt. Eng., Vol. 46, 086202, 2007.
, A. B. and J. W. van Ness, SIAM Review, Vol. 10, 422-437, 1968.

42. Leung, H. and T. Lo, "A spatial temporal dynamical model for multipath scattering from the sea," IEEE Trans. Geosci. Remote Sensing, Vol. 33, 441-448, 1995.

43. Leung, H., N. Dubash, and N. Xie, "Detection of small objects in clutter using a GA-RBF neural network," IEEE Transactions on Aerospace and Electronic Systems, Vol. 38, 98-118, 2002.

44. Tzeng, Y. C. and K. S. Chen, "Change detection in synthetic aperture radar images using a spatially chaotic model," Opt. Eng., Vol. 46, 086202, 2007.

45. Chou, N. S., Y. C. Tzeng, K. S. Chen, C. T. Wang, and K. C. Fan, "On the application of a spatial chaotic model for detecting landcover changes in synthetic aperture radar images," J. Appl. Rem. Sens., Vol. 3, 033512-1-16, 2009.

46. Mallat, S. G., "A theory for multiresolution signal decomposition: The wavelet representation," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 11, 674-693, 1989.

47. Mallat, S., A Wavelet Tour of Signal Processing, 2nd Ed., Academic Press, 1999.

48. Brown, R. and P. Hwang, Introduction to Random Signal Analysis and Kalman Filtering, Wiley, New York, 1983.