The scattering center extraction algorithm is a method to estimate the scattering center from the backscattered field. Superior scattering center extraction algorithms should be robust to noise, independent of the model order, and automatically and quickly operated. In this paper, we propose a novel super resolution scattering center extraction algorithm that satisfies the conditions mentioned above, which has been named the dimension reduced optimization problem (DROP). Using DROP, we determined a one-dimensional scattering center from a high resolution range profile and a two-dimensional scattering center from an inverse synthetic aperture radar image.
2. Kim, I. H., I. S. Choi, and D. Y. Chae, "A study on the performance enhancement of radar target classification using the two-level feature vector fusion method," Journal of Electromagnetic Engineering and Science, Vol. 18, No. 3, 206-211, Jul. 2018.
doi:10.26866/jees.2018.18.3.206
3. Hurst, M. and R. Mittra, "Scattering center analysis via Prony’s method," IEEE Transactions on Antennas and Propagation, Vol. 35, No. 8, 986-988, Aug. 1987.
doi:10.1109/TAP.1987.1144210
4. Pillai, S. U. and B. H. Kwon, "GEESE (GEneralized Eigenvalues Utilizing Signal Subspace Eignevectors) --- A new technique for direction finding," Twenty-second Asilomar Conference on Signals, Systems and Computers, Vol. 2, 568-572, 1988.
doi:10.1109/ACSSC.1988.754606
5. Roy, R. and T. Kailath, "ESPRIT-estimation of signal parameters via rotational invariance techniques," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No. 7, 984-995, Jul. 1989.
doi:10.1109/29.32276
6. Hua, Y., "On SVD for estimating generalized eigenvalues of singular matrix pencil in noise," IEEE Transactions on Signal Processing, Vol. 39, No. 4, 9, 1991.
doi:10.1109/78.80911
7. Hua, Y., "Estimating two-dimensional frequencies by matrix enhancement and matrix pencil," IEEE Transactions on Signal Processing, Vol. 40, 2267-2280, Sep. 1992.
doi:10.1109/78.157226
8. Rouquette, S. and M. Najim, "Estimation of frequencies and damping factors by two-dimensional ESPRIT type methods," IEEE Transactions on Signal Processing, Vol. 49, No. 1, 2001.
doi:10.1109/78.890367
9. Quinquis, A., E. Radoi, and F.-C. Totir, "Some radar imagery results using superresolution techniques," IEEE Transactions on Antennas and Propagation, Vol. 52, No. 5, 1230-1244, May 2004.
doi:10.1109/TAP.2004.827541
10. Li, Q., E. J. Rothwell, K.-M. Chen, and D. P. Nyquist, "Scattering center analysis of radar targets using fitting scheme and genetic algorithm," IEEE Transactions on Antennas and Propagation, Vol. 44, No. 2, 198-207, Feb. 1996.
doi:10.1109/8.481648
11. Choi, I. S. and H. T. Kim, "One-dimensional evolutionary programming-based CLEAN," Electronics Letters, Vol. 37, No. 6, 400-401, Mar. 2001.
doi:10.1049/el:20010259
12. Choi, I.-S. and H.-T. Kim, "Two-dimensional evolutionary programming-based CLEAN," IEEE Transactions on Aerospace and Electronic Systems, Vol. 39, No. 1, 373-382, Jan. 2003.
doi:10.1109/TAES.2003.1188920
13. Choi, I.-S. and H.-T. Kim, "Generalized early-time/late-time evolutionary programming-based CLEAN," Microwave and Optical Technology Letters, Vol. 50, No. 1, 208-210, Jan. 2008.
doi:10.1002/mop.23032
14. Schwarz, U. J., "Mathematical-statistical description of the iterative beam removing technique (method CLEAN)," Astron. Astrophy., Vol. 65, 345-356, 1978.
15. Choi, I.-S., "Performance comparison of PSO-based CLEAN and EP-based CLEAN for scattering center extraction," Ubiquitous Computing and Multimedia Applications, Vol. 150, 139-146, 2011.
doi:10.1007/978-3-642-20975-8_15
16. Armijo, L., "Minimization of functions having Lipschitz continuous first partial derivatives," Pacific Journal of Mathematics, Vol. 16, No. 1, 1-3, Jan. 1966.
doi:10.2140/pjm.1966.16.1
17. Choi, Y.-J. and I.-S. Choi, "A novel fast clean algorithm using the gradient descent method," Microwave and Optical Technology Letters, Vol. 59, No. 5, 1018-1022, May 2017.
doi:10.1002/mop.30448
18. Bydder, M., "Solution of a complex least squares problem with constrained phase," Linear Algebra and Its Applications, Vol. 433, 1719-1721, Dec. 2010.
doi:10.1016/j.laa.2010.07.011
19. Ozdemir, C., Inverse Synthetic Aperture Radar Imaging with MATLAB, Wiley, Etobicoke, ON, Canada, 2012.
doi:10.1002/9781118178072
20. Cho, B.-L., I.-S. Choi, and E. J. Rothwell, "Enhanced ISAR imaging method using back-projection and SVA algorithm," Microwave and Optical Technology Letters, Vol. 57, No. 4, 993-997, 2015.
doi:10.1002/mop.28993
21. Rezaiesarlak, R. and M. Manteghi, "Complex-natural-resonance-based design of chipless RFID tag for high-density data," IEEE Transactions on Antennas and Propagation, Vol. 62, No. 2, 898-904, Feb. 2014.
doi:10.1109/TAP.2013.2290998
22. Thirion-Lefevre, L. and E. Colin-Koeniguer, "Investigating attenuation, scattering phase center, and total height using simulated interferometric SAR images of forested areas," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 10, 3172-3179, Oct. 2007.
doi:10.1109/TGRS.2007.904921