Skip to main content
EURASIP Journal on Advances in Signal Processing
Download PDF
  • Research Article
  • Open access
  • Published:

Fast Iterative Subspace Algorithms for Airborne STAP Radar

EURASIP Journal on Advances in Signal Processing volume 2006, Article number: 037296 (2006) Cite this article

Abstract

Space-time adaptive processing (STAP) is a crucial technique for the new generation airborne radar for Doppler spread compensation caused by the platform motion. We here propose to apply range cell snapshots-based recursive algorithms in order to reduce the computational complexity of the conventional STAP algorithms and to deal with a possible nonhomogeneity of the data samples. Subspace tracking algorithms as PAST, PASTd, OPAST, and more recently the fast approximate power iteration (FAPI) algorithm, which are time-based recursive algorithms initially introduced in spectral analysis, array processing, are good candidates. In this paper, we more precisely investigate the performance of FAPI for interference suppression in STAP radar. Extensive simulations demonstrate the outperformance of FAPI algorithm over other subspace trackers of similar computational complexity. We demonstrate also its effectiveness using measured data from the multichannel radar measurements (MCARM) program.

References

  1. Klemm R: Space-Time Adaptive Processing: Principles and Applications, IEE Radar, Sonar, Navigation and Avionics. Volume 9. IEE Press, London, UK; 2000.

    Google Scholar 

  2. Skolnik MI: Radar Handbook. McGraw-Hill, New York, NY, USA; 1990.

    Google Scholar 

  3. Brennan LE, Reed LS: Theory of adaptive radar. IEEE Transactions on Aerospace and Electronic Systems 1973, 9(2):237–252.

    Article  Google Scholar 

  4. Haimovich A: Eigencanceler: adaptive radar by eigenanalysis methods. IEEE Transactions on Aerospace and Electronic Systems 1996, 32(2):532–542.

    Article  Google Scholar 

  5. Hua Y, Xiang Y, Chen T, Abed-Meraim K, Miao Y: A new look at the power method for fast subspace tracking. Digital Signal Processing 1999, 9(4):297–314. 10.1006/dspr.1999.0348

    Article  Google Scholar 

  6. Badeau R, David B, Richard G: Fast approximated power iteration subspace tracking. IEEE Transactions on Signal Processing 2005, 53(8):2931–2941.

    Article  MathSciNet  Google Scholar 

  7. Yang B: Projection approximation subspace tracking. IEEE Transactions on Signal Processing 1995, 43(1):95–107. 10.1109/78.365290

    Article  Google Scholar 

  8. Abed-Meraim K, Chkeif A, Hua Y: Fast orthonormal PAST algorithm. IEEE Signal Processing Letters 2000, 7(3):60–62. 10.1109/97.823526

    Article  Google Scholar 

  9. Himed B: MCARM/STAP data analysis. In Tech. Rep. AFRL-SN-RS-TR-1999-48. Air Force Research Laboratory, Dayton, Ohio, USA; May 1999. Vol II

    Google Scholar 

  10. Ward J: Space-time adaptive processing for airborne radar. In Tech. Rep. 1015. MIT Lincoln Laboratory, Lexington, Mass, USA; December 1994.

    Google Scholar 

  11. Richardson PG: STAP covariance matrix structure and its impact on clutter plus jamming suppression solutions. Electronics Letters 2001, 37(2):118–119. 10.1049/el:20010090

    Article  Google Scholar 

  12. Hua Y: Asymptotical orthonormalization of subspace matrices without square root. IEEE Signal Processing Magazine 2004, 21(4):56–61. 10.1109/MSP.2004.1311143

    Article  MathSciNet  Google Scholar 

  13. Jung-Lang Y: A novel subspace tracking using correlation-based projection approximation. Signal Processing 2000, 80(12):2517–2525. 10.1016/S0165-1684(00)00138-9

    Article  Google Scholar 

  14. Kamenetsky M, Widrow B: A variable leaky LMS adaptive algorithm. Proceedings of the IEEE conference of the 38th Asilomar on Signals, Systems and Computers, November 2004, Pacific Grove, Calif, USA 1: 125–128.

    Google Scholar 

  15. Kim YL, Pillai SU, Guerci JR: Optimal loading factor for minimal sample support space-time adaptive radar. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '98), May 1998, Seattler, Wash, USA 4: 2505–2508.

    Google Scholar 

  16. Goldstein JS, Reed IS, Zulch PA: Multistage partially adaptive stap cfar detection algorithm. IEEE Transaction on Aerospace and Electronic Systems 1999, 35(2):645–662. 10.1109/7.766945

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratoire des Signaux et Systèmes (LSS), CNRS, Supélec, 3 rue Joliot-Curie, Plateau du Moulon, Gif-sur-Yvette Cedex, 91192, France

    Hocine Belkacemi & Sylvie Marcos

Authors
  1. Hocine Belkacemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sylvie Marcos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hocine Belkacemi.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Belkacemi, H., Marcos, S. Fast Iterative Subspace Algorithms for Airborne STAP Radar. EURASIP J. Adv. Signal Process. 2006, 037296 (2006). https://doi.org/10.1155/ASP/2006/37296

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1155/ASP/2006/37296

Keywords