volume | PIER Journals

Abstract

This research introduces compressed sensing (CS) principle into inverse synthetic aperture radar (ISAR) imaging of non-uniform rotation targets, and high azimuth resolution can be achieved with limited number of pulses. Firstly, the sparsity of the echoed signal of radar targets with non-uniform rotation in certain matching Fourier domain is analyzed. Then the restricted isometry property (RIP) and incoherence of partial matching Fourier matrices are checked, following which an ISAR imaging method based on CS for both random sparse aperture and short aperture cases is proposed. In particular, considering the dependence of the sparse dictionary on the relative rotation parameter, a parameter estimation method by the optimal search in fractional Fourier domain is presented. Simulation experiments verify the effectiveness as well as superiority of the proposed imaging method over traditional methods in terms of imaging performance.

1. Bao, Z., M. D. Xing, and T. Wang, Radar Imaging Technique, Publishing House of Electronics Industry, 2006.

2. Donoho, D. L., "Compressed sensing," IEEE Trans. Inform. Theory, Vol. 52, No. 4, 1289-1306, 2006.
doi:10.1109/TIT.2006.871582 Google Scholar

3. Candes, E. and M. Wakin, "An introduction to compressive sampling," IEEE Sig. Proc. Mag., Vol. 25, No. 2, 21-30, 2008.
doi:10.1109/MSP.2007.914731 Google Scholar

4. Ender, J. H. G., "On compressive sensing applied to radar," Signal Processing, Vol. 90, No. 5, 1402-1414, 2010.
doi:10.1016/j.sigpro.2009.11.009 Google Scholar

5. Potter, L. C., E. Ertin, J. T. Parker, and M. Cetin, "Sparsity and compressed sensing in radar imaging," Proceedings of the IEEE, Vol. 98, No. 62, 1006-1020, 2010.
doi:10.1109/JPROC.2009.2037526 Google Scholar

6. Wei, S.-J., X.-L. Zhang, and J. Shi, "Linear array SAR imaging via compressed sensing," Progress In Electromagnetics Research, Vol. 117, 299-319, 2011. Google Scholar

7. 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.
doi:10.2528/PIER10080805 Google Scholar

8. 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, 2012. Google Scholar

9. Li, J., S. Zhang, and J. Chang, "Applications of compressed sensing for multiple transmitters multiple azimuth beams SAR imaging," Progress In Electromagnetics Research, Vol. 127, 259-275, 2012.
doi:10.2528/PIER12021307 Google Scholar

10. Zhang, L., M. D. Xing, C. W. Qiu, J. Li, and Z. Bao, "Achieving higher resolution ISAR imaging with limited pulses via compressed sampling," IEEE Geosci. Remote Sens. Lett., Vol. 6, No. 3, 567-571, 2009.
doi:10.1109/LGRS.2009.2021584 Google Scholar

11. Zhang, L., M. D. Xing, C. W. Qiu, et al. "Resolution enhancement for inversed synthetic aperture radar imaging under low SNR via improved compressive sensing," IEEE Trans. Geosci. Remote Sens., Vol. 48, No. 10, 3824-3838, 2010.
doi:10.1109/TGRS.2010.2048575 Google Scholar

12. Rao, W., G. Li, X. Q. Wang, and X.-G. Xia, "ISAR imaging of maneuvering targets with missing data via matching pursuit," Proceedings of IEEE Radar Conference, 124-128, 2011. Google Scholar

13. Quan, Y. H., L. Zhang, R. Guo, M. D. Xing, Z. Bao, "Generating dense and super-resolution ISAR image by combining bandwidth extrapolation and compressive sensing," SCIENCE CHINA Information Sciences, Vol. 54, No. 10, 2158-2169, 2011.
doi:10.1007/s11432-011-4298-4 Google Scholar

14. Zhao, G. H., Z. Y. Wang, Q. Wang, G. M. Shi, and F. F. Shen, "Robust ISAR imaging based on compressive sensing from noisy measurements," Signal Processing, Vol. 92, No. 1, 120-129, 2012.
doi:10.1016/j.sigpro.2011.06.011 Google Scholar

15. Li, J., M. D. Xing, and S. J. Wu, "Application of compressed sensing in sparse aperture imaging of radar," Proceedings of 2nd Asian-Paci¯c Conf. on Synthetic Aperture Radar (APSAR'09), 1119-1119, Oct. 2009. Google Scholar

16. Raghu, G. R. and F. Masoud, "ISAR imaging in sea clutter via compressive sensing," International Conference on Waveform Diversity and Design Conference (WDD), 200-205, Aug. 2010. Google Scholar

17. Raghu, G. R., C. C. Victor, and L. Ronald, "A greedy approach for sparse angular aperture radar," Proceedings of IEEE Radar Conference, 673-677, 2010. Google Scholar

18. Fu, Y. W., J. M. Hu, and X. Li, "ISAR imaging of uniform accelerative rotating targets based on chirp-Fourier transform," Systems Engineering and Electronics, Vol. 33, No. 12, 2608-2612, 2011. Google Scholar

19. Yin, Z. P., "Applications of fractional Fourier transform to inverse synthetic aperture radar imaging processing,", Ph.D. thesis, University of Science and Technology of China, Hefei, 2008. Google Scholar

20. Liu, A. F., X. H. Zhu, J. H. Lu, and Z. Liu, "Imaging in inverse synthetic aperture radar (ISAR) based on discrete matching Fourier transform," Acta Armamentarii, Vol. 25, No. 4, 458-462, 2004. Google Scholar

21. Huang, Y. J., M. Cao, Y. W. Fu, Y. N. Li, and W. D. Jiang, "ISAR imaging of equably accelerative rotating targets based on matching Fourier transform," Signal Processing, Vol. 25, No. 6, 864-867, 2009. Google Scholar

22. Cao, M., "Research on high resolution radar imaging technology for space targets,", Ph.D. thesis, National University of Defense Technology, Changsha, 2009. Google Scholar

23. Liu, J. H., H., X. Li, Y. L. Qin, and Z. W. Zhuang, "ISAR imaging of non-uniform rotation targets via compressed sensing based on sparsity in matching fourier domain," 1st International Workshop on Compressed Sensing applied to Radar, May 2012. Google Scholar

24. Wang, S. L., S. G. Li, J. L. Ni, and G. Y. Zhang, "A new transform --- Match Fourier transform," Acta Electronica Sinica, Vol. 29, No. 3, 403-405, 2001. Google Scholar

25. Wang, S. L., "A new method for radar signal processing-matched Fourier transform,", Ph.D. thesis, Xidian University, Xi'an, 2003. Google Scholar

26. Applebaum, L., S. Howard, S. Searle, and R. Calderbank, "Chirp sensing codes: Deterministic compressed sensing measurements for fast recovery," Applied and Computational Harmonic Analysis, Vol. 26, No. 2, 283-290, 2009. Google Scholar

27. Patel, V. M., G. R. Easley, D. M. Healy, and R. Chellappa, "Compressed synthetic aperture radar," IEEE Journal of Selected Topics in Signal Processing, Vol. 4, No. 2, 244-254, 2010. Google Scholar

28. Duarte, M. F., Y. C. Eldar, and R. Chellappa, "Structured compressed sensing: From theory to applications," IEEE Trans. Signal Process., Vol. 59, No. 9, 4053-4085, 2011. Google Scholar

29. Saxena, R. and K. Singh, "Fractional Fourier transform: A novel tool for signal processing," J. Indian Inst. Sci., Vol. 85, 11-26, 2005. Google Scholar

30. Gerald, C. F. and P. O. Wheatley, Applied Numerical Analysis, 7th Ed., Pearson/Addison-Wesley, 2004.

31. Mohimani, H., M. Babaie-Zadeh, and C. Jutten, "A fast approach for overcomplete sparse decomposition based on smoothed l0 norm," IEEE Trans. Signal Process., Vol. 57, No. 1, 289-301, 2009. Google Scholar

Dr. Jihong Liu

Dr. Xiang Li

Dr. Shaokun Xu

Dr. Zhaowen Zhuang