volume | PIER Journals

Abstract

The noise effect is very challenging in radar target recognition. It usually degrades the accuracy of target recognition and then makes the recognition unreliable. In this study, we present a noise-reduction technique to improve the accuracy of radar target recognition. Our noise-reduction technique is based on the SVD (singular value decomposition). The PCA (principal components analysis) based radar recognition algorithm is utilized to verify our noise-reduction scheme. In our treatment, the received signals are arranged into a Hankel-form matrix. This Hankel-form matrix is decomposed into two subspaces, i.e., the noise-related subspace and clean-signal subspace. The noise reduction is obtained by suppressing the noise-related subspace and retaining the clean-signal space only. Simulation results show that the accuracy of target recognition is greatly improved as the received signals are first processed by the SVD noise-reduction technique. With the use of proposed noise-reduction scheme, the radar target recognition can tolerate more noises and then becomes more reliable. The noise-reduction technique in this study can also be applied to many other problems in radar engineering.

1. Hajduch G., J. M. Le Caillec and and R. Garello, "Airborne high-resolution ISAR imaging of ship targets at sea," IEEE Transactions on Aerospace and Electronic Systems, Vol. 40, No. 1, 378-384, 2004.
doi:10.1109/TAES.2004.1292177 Google Scholar

2. Tello, M., C. Lopez-Martinez, and J. J. Mallorqui, "A novel algorithm for ship detection in SAR imagery based on the wavelet transform," IEEE Geoscience and Remote Sensing Letters, Vol. 2, No. 2, 201-205, 2005.
doi:10.1109/LGRS.2005.845033 Google Scholar

3. Farhat, N. H., "Microwave diversity imaging and automated target identification based on models of neural networks," IEEE Proceedings, Vol. 77, No. 5, 670-681, 1989.

4. Moon, T. K. and W. C. Stirling, Mathematical Methods and Algorithms for Signal Processing, Prentice Hall, 2000.

5. Duda, R. O., P. E. Hart, and D. G. Stork, Pattern Classification, 2nd edition, 2001.

6. Lee, K. C., J. S. Ou, and C. H. Huang, "Angular-diversity radar recognition of ships by transformation based approaches — including noise effects," Progress In Electromagnetics Research, Vol. 72, 145-158, 2007.
doi:10.2528/PIER07030901 Google Scholar

7. Jensen, S. H., P. C. Hansen, S. D. Hansen, and J. A. Sorensen, "Reduction of broad-band noise in speech by truncated QSVD," IEEE Transactions on Speech and Audio Processing, Vol. 3, 439-448, 1995.
doi:10.1109/89.482211 Google Scholar

8. Hermus, K.I. Dologlou, P. Wambacq, and D. V. Compernolle, "Fully adaptive svd-based noise removal for robust speech recognition," European Conference on Speech Communication and Technology, 1951-1954, 1999.

9. Konstantinides, K., B. Natarajan, and G. S. Yovanof, "Noise estimation and filtering using blockbased singular value decomposition," IEEE Transactions on Image Processing, Vol. 6, 479-483, 1997.
doi:10.1109/83.557359 Google Scholar

10. Ruck, G. T., D. E. Barrick, W. D. Stuart, and C. K. Krichbaum, Radar Cross Section Handbook, Vol. 1, Vol. 1, 1970.

11. Cui, B., J. Zhang, and X. W. Sun, "Single layer microstrip antenna arrays applied in millimeter-wave radar front-end," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 1, 3-15, 2008.
doi:10.1163/156939308783122797 Google Scholar

12. Xue W. and X. W. Sun "Target detection of vehicle volume detecting radar based on Wigner-Hough transform," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 11, 1513-1523, 2007. Google Scholar

13. Wang, C. J., B. Y. Wen, Z. G. Ma, W. D. Yan, and X. J. Huang, "Measurement of river surface currents with UHF FMCW radar systems," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 3, 375-386, 2007.
doi:10.1163/156939307779367350 Google Scholar

14. Jung, J. H., H. T. Kim, and K. T. Kim, "Comparisons of four feature extraction approaches based on Fisher's linear discriminant criterion in radar target recognition," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 2, 251-265, 2007.
doi:10.1163/156939307779378781 Google Scholar

15. Wang, S. G., X. P. Guan, X. Y. Ma, D. W. Wang, and Y. Su, "Calculating the poles of complex radar targets," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 14, 2065-2076, 2065.
doi:10.1163/156939306779322657 Google Scholar

16. Alivizatos, E. G., M. N. Petsios, and N. K. Uzunoglu, "Towards a range-doppler UHF multistatic radar for the detection of noncooperative targets with low RCS," Journal of Electromagnetic Waves and Applications, Vol. 19, No. 15, 2015-2031, 2005.
doi:10.1163/156939305775570512 Google Scholar

17. Capineri, L., D. Daniels, P. Falorni, O. Lopera, and C. Windsor, "Estimation of relative permittivity of shallow soils by using the ground penetrating radar response from different buried targets," Progress In Electromagnetics Research Letters, Vol. 2, 63-71, 2008. Google Scholar

18. Abdelaziz, A. A., "Improving the performance of an antenna array by using radar absorbing cover," Progress In Electromagnetics Research Letters, Vol. 1, 129-138, 2008.
doi:10.2528/PIERL07112503 Google Scholar

19. Razevig, V. V., S. I. Ivashov, A. P. Sheyko, I. A. Vasilyev, and A. V. Zhuravlev, "An example of holographic radar using at restoration works of historical building," Progress In Electromagnetics Research Letters, Vol. 1, 173-179, 2008.
doi:10.2528/PIERL07120603 Google Scholar

20. Hebeish, A. A., M. A. Elgamel, R. A. Abdelhady, and A. A. Abdelaziz, "Factors affecting the performance of the radar absorbant textile materials of different types and structus," Progress In Electromagnetics Research B, Vol. 3, 219-226, 2008.
doi:10.2528/PIERB07121702 Google Scholar

21. Chan, Y. K. and V. C. Koo, "An introduction to synthetic aperture radar (SAR)," Progress In Electromagnetics Research B, Vol. 2, 27-60, 2008.
doi:10.2528/PIERB07110101 Google Scholar

Professor Kun-Chou Lee

Dr. Jhih-Sian Ou

Dr. Ming-Chung Fang