Circular synthetic aperture radar (CSAR) imaging based on compressive sensing with random step frequency (RSF) as transmitted signal is introduced. CSAR is capable of obtaining both two-dimensional high resolution image and three-dimensional image due to a circular collection trajectory. RSF signal shares good characteristics of noise signals including ``thumbtack-shape" ambiguity function, low probability of interception, and strong anti-jamming capability. As a result, CSAR adopting RSF signal can make use of advantages of both CSAR and RSF signal. Compressive sensing is a new data acquisition and reconstruction theorem for sparse or compressible signals, which needs fewer samples to reconstruct signals than traditional Nyquist theorem. Simulation results show that both two-dimensional and three-dimensional targets can be well reconstructed from few samples by applying compressive sensing to RSF CSAR imaging.
2. Bryant, M. L., L. L. Gostin, and M. Soumekh, "Three-dimensional E-CSAR imaging of a T-72 tank and synthesis of its spotlight, stripmap and interferometric SAR reconstructions," International Conference on Image Processing, 628-631, 2001.
3. Bryant, M. L., L. L. Gostin, and M. Soumekh, "3-D E-CSAR maging of a T-72 tank and synthesis of its SAR reconstructions," IEEE Transactions on Aerospace and Electronic Systems, Vol. 39, No. 1, 211-227, 2003.
4. Cantalloube, H. M. J., P. Dubois-Fernandez, and X. Dupuis, "Very high resolution SAR images over dense urban area," IEEE International Geoscience and Remote Sensing Symposium, Vol. 4, 2799-2802, 2005.
5. Cantalloube, H. and E. C. Koeniguer, "Assessment of physical limitations of high resolution on targets at X-band from circular SAR experiments," European Conference on Synthetic Aperture Radar, June 2008.
6. Oriot, H. and H. Cantalloube, "Circular SAR imagery for urban remote sensing," European Conference on Synthetic Aperture Radar, June 2008.
7. Palm, S. and H. Oriot, "DEM extraction over urban area using circular SAR imagery," European Conference on Synthetic Aperture Radar, June 2008.
8. Frölind, P.-O. U., M. H. Lars, and A. Gustavsson, "First results on VHF-band SAR imaging using circular tracks," European Conference on Synthetic Aperture Radar, June 2008.
9. Tan, W. X., et al., "Circular SAR experiment for human body imaging," Asian and Pacific Conference on Synthetic Aperture Radar, 90-93, 2007.
10. Tan, W. X., W. Hong, Y. P. Wang, and Y. R. Wu, "A novel spherical-wave three-dimensional imaging algorithm for microwave cylindrical scanning geometries," Progress In lectromagnetics Research, Vol. 111, 43-70, 2011.
11. Axelsson, S. R. J., "Random noise radar/sodar with ultrawide-band waveforms," IEEE Transactions on Geoscience and Remote Sensing , Vol. 45, No. 5, 1099-1114, 2007.
12. Axelsson, S. R. J., "Analysis of random step frequency radar and comparison with experiments," IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 4, 890-904, 2007.
13. Candes, E. J., J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Transactions on Information Theory, Vol. 52, No. 2, 489-509, 2006.
14. Donoho, D. L., "IEEE Transactions on Information Theory,", Vol. 52, No. 4, 1289-1306, 2006.
15. Candes, E. J. and T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies?," IEEE Transactions on Information Theory, Vol. 52, No. 2, 5406-5425, 2006.
16. Baraniuk, R. and P. Steeghs, "Compressive radar imaging," IEEE Radar Conference, 128-133, 2007.
17. Zhu, X. X. and R. Bamler, "Compressive sensing for high resolution differential SAR tomography-the SL1MMER algorithm," IEEE International Geoscience and Remote Sensing Symposium, 17-20, 2010.
18. 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.
19. Li, J., S. S. Zhang, and J. F. Chang, "Applications of compressed sensing for multiple transmitters multiple azimuth beams SAR imaging," Progress In Electromagnetics Research, Vol. 127, 259-275, 2012.
20. Liu, Z., X. Z. Wei, and X. Li, "Adaptive clutter suppression for airborne random pulse repretition interval radar based on compressed sensing," Progress In Electromagnetics Research, Vol. 128, 291-131, 2012.
21. Lin, Y., et al., "Compressed sensing technique for circular SAR imaging," IET International Radar Conference, April 2009.
22. Chen, S. S., D. L. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM Journal on Scientific Computing, Vol. 20, No. 1, 33-61, 1998.
23. Birgin, E. G., J. M. Martínez, and M. Raydan, "Nonmonotone spectral projected gradient methods on convex sets," SIAM Journal on Optim., Vol. 10, No. 4, 1196-1211, 2000.