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International Journal of Antennas and Propagation
Volume 2014, Article ID 196507, 14 pages
http://dx.doi.org/10.1155/2014/196507
Research Article

Knowledge-Aided STAP Using Low Rank and Geometry Properties

1Research Institute of Space Electronics, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, China
2Communications Research Group, Department of Electronics, University of York, York YO10 5DD, UK

Received 27 April 2014; Accepted 17 July 2014; Published 12 August 2014

Academic Editor: Hang Hu

Copyright © 2014 Zhaocheng Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Ward, “Space-time adaptive processing for airborne radar,” Tech. Rep. 1015, MIT Lincoln Laboratory, Lexington, Mass, USA, 1994. View at Google Scholar
  2. R. Klemm, Principles of Space-Time Adaptive Processing, Institute of Electical Engineering, London, UK, 2006.
  3. J. R. Guerci, Space-time Adaptive Processing for Radar, Artech House, 2003.
  4. W. L. Melvin, “A STAP overview,” IEEE Aerospace and Electronic Systems Magazine, vol. 19, no. 1, pp. 19–35, 2004. View at Publisher · View at Google Scholar · View at Scopus
  5. A. M. Haemovich and M. Berin, “Eigenanalysis-based space-time adaptive radar: performance analysis,” IEEE Transactions on Aerospace and Electronic Systems, vol. 33, no. 4, pp. 1170–1179, 1997. View at Publisher · View at Google Scholar · View at Scopus
  6. J. R. Guerci and J. S. Bergin, “Principal components, covariance matrix tapers, and the subspace leakage problem,” IEEE Transactions on Aerospace and Electronic Systems, vol. 38, no. 1, pp. 152–162, 2002. View at Publisher · View at Google Scholar · View at Scopus
  7. H. Wang and L. Cai, “On adaptive spatial-temporal processing for airborne surveillance radar systems,” IEEE Transactions on Aerospace and Electronic Systems, vol. 30, no. 3, pp. 660–670, 1994. View at Publisher · View at Google Scholar · View at Scopus
  8. R. C. de Lamare, L. Wang, and R. Fa, “Adaptive reduced-rank LCMV beamforming algorithms based on joint iterative optimization of filters: Design and analysis,” Signal Processing, vol. 90, no. 2, pp. 640–652, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  9. R. Fa, R. C. de Lamare, and L. Wang, “Reduced-rank STAP schemes for airborne radar based on switched joint interpolation, decimation and filtering algorithm,” IEEE Transactions on Signal Processing, vol. 58, no. 8, pp. 4182–4194, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  10. R. Fa and R. C. de Lamare, “Reduced-rank STAP algorithms using joint iterative optimization of filters,” IEEE Transactions on Aerospace and Electronic Systems, vol. 47, no. 3, pp. 1668–1684, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. J. R. Román, M. Rangaswamy, D. W. Davis, Q. Zhang, B. Himed, and J. H. Michels, “Parametric adaptive matched filter for airborne radar applications,” IEEE Transactions on Aerospace and Electronic Systems, vol. 36, no. 2, pp. 677–692, 2000. View at Publisher · View at Google Scholar · View at Scopus
  12. Z. Yang, R. C. de Lamare, and X. Li, “L1-regularized STAP algorithms with a generalized sidelobe canceler architecture for airborne radar,” IEEE Transactions on Signal Processing, vol. 60, no. 2, pp. 674–686, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  13. Z. Yang, R. C. de Lamare, and X. Li, “Sparsity-aware space-time adaptive processing algorithms with L1-norm regularisation for airborne radar,” IET Signal Processing, vol. 6, no. 5, pp. 413–423, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  14. Z. Yang, X. Li, H. Wang, and W. Jiang, “On clutter sparsity analysis in space-time adaptive processing airborne radar,” IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 5, pp. 1214–1218, 2013. View at Publisher · View at Google Scholar · View at Scopus
  15. Z. Yang, X. Li, H. Wang, and W. Jiang, “Adaptive clutter suppression based on iterative adaptive approach for airborne radar,” Signal Processing, vol. 93, no. 12, pp. 3567–3577, 2013. View at Publisher · View at Google Scholar · View at Scopus
  16. Z. Yang, X. Li, H. Wang, and L. Nie, “Sparsity-based space-time adaptive processing using complex-valued homotopy technique for airborne radar,” IET Signal Processing, vol. 8, no. 5, pp. 552–564, 2014. View at Publisher · View at Google Scholar
  17. J. R. Guerci and E. J. Baranoski, “Knowledge-aided adaptive radar at DARPA,” IEEE Signal Processing Magazine, vol. 23, no. 1, pp. 41–50, 2006. View at Publisher · View at Google Scholar · View at Scopus
  18. M. C. Wicks, M. Rangaswamy, R. Adve, and T. B. Hale, “Space-time adaptive processing,” IEEE Signal Processing Magazine, vol. 23, no. 1, pp. 51–65, 2006. View at Publisher · View at Google Scholar · View at Scopus
  19. W. L. Mevin and G. A. Showman, “An approach to knowledge-aided covariance estimation,” IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 3, pp. 1021–1042, 2006. View at Google Scholar
  20. W. Xie, K. Duan, F. Gao, Y. Wang, and Z. Zhang, “Clutter suppression for airborne phased radar with conformal arrays by least squares estimation,” Signal Processing, vol. 91, no. 7, pp. 1665–1669, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  21. I. W. Selesnick, S. U. Pillai, K. Y. Li, and B. Himed, “Angle-Doppler processing using sparse regularization,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '10), pp. 2750–2753, March 2010. View at Publisher · View at Google Scholar · View at Scopus
  22. C. Chen and P. P. Vaidyanathan, “MIMO radar space-time adaptive processing using prolate spheroidal wave functions,” IEEE Transactions on Signal Processing, vol. 56, no. 2, pp. 623–635, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  23. P. Stoica, J. Li, X. Zhu, and J. Guerci, “On using a priori knowledge in space-time adaptive processing,” IEEE Transactions on Signal Processing, vol. 56, no. 6, pp. 2598–2602, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. J. R. Guerci, Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, Artech House, London, UK, 2010.
  25. J. S. Bergin, P. M. Techau, W. L. Melvin, and J. R. Guerci, “GMTI STAP in target-rich environments: site-specific analysis,” in Proceedings of the IEEE Radar Conference, pp. 391–396, Long Beach, Calif, USA, April 2002. View at Scopus
  26. J. S. Bergin, C. M. Teixeira, P. M. Techau, and J. R. Guerci, “Improved clutter mitigation performance using knowledge-aided space-time adaptive processing,” IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 3, pp. 997–1008, 2006. View at Publisher · View at Google Scholar · View at Scopus
  27. E. Conte, A. de Maio, A. Farina, and G. Foglia, “Design and analysis of a knowledge-aided radar detector for Doppler processing,” IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 3, pp. 1058–1079, 2006. View at Publisher · View at Google Scholar · View at Scopus
  28. K. Gerlach and M. L. Picciolo, “Airborne/spacebased radar STAP using a structured covariance matrix,” IEEE Transactions on Aerospace and Electronic Systems, vol. 39, no. 1, pp. 269–281, 2003. View at Publisher · View at Google Scholar · View at Scopus
  29. X. Zhu, J. Li, and P. Stoica, “Knowledge-aided space-time adaptive processing,” IEEE Transactions on Aerospace and Electronic Systems, vol. 47, no. 2, pp. 1325–1336, 2011. View at Publisher · View at Google Scholar · View at Scopus
  30. R. Fa, R. C. de Lamare, and V. H. Nascimento, “Knowledge-aided STAP algorithm using convex combination of inverse covariance matrices for heterogenous clutter,” in Proceeding of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '10), pp. 2742–2745, Dallas, Tex, USA, March 2010. View at Publisher · View at Google Scholar · View at Scopus
  31. Q. Zhang and W. B. Mikhael, “Estimation of the clutter rank in the case of subarraying for space-time adaptive processing,” Electronics Letters, vol. 33, no. 5, pp. 419–420, 1997. View at Publisher · View at Google Scholar · View at Scopus
  32. N. A. Goodman and J. M. Stiles, “On clutter rank observed by arbitrary arrays,” IEEE Transactions on Signal Processing, vol. 55, no. 1, pp. 178–186, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  33. R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, Cambridge, UK, 1985. View at Publisher · View at Google Scholar · View at MathSciNet