Adaptive Linearly Constrained Beamforming Algorithms for Smart Jamming Suppression

  • Shiunn-Jang Chern
Part of the Signals and communication technology book series (SCT)


To suppress the smart jamming efficiently, in this paper, array beamforming algorithms, based on direct linearly constrained as well as the so-called Generalized Sidelobe Canceller (GSC) structures, are addressed. The performance comparison between different structures with variety adaptation algorithms is emphasized. Especially, we will focus on the capability of smart jamming suppression with the modified conjugate gradient algorithm, which is one of the conjugate direction techniques, in such environments when the pointing error is existed. The merits of different constrained algorithms are verified by evaluating the performance, in terms of the output signal-to-interference ratio (SINR) to investigate the convergence property and beampatterns to verify the nulling capability.


Weight Vector Conjugate Gradient Azimuth Angle Conjugate Gradient Algorithm Adaptive Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    O. L. Frost III, “An Algorithm for Linearly-Constrained Adaptive Array Processing,” Proc. IEEE, vol. 60, pp. 926–935, Aug. 1972CrossRefGoogle Scholar
  2. 2.
    S. Haykin, Adaptive Filter Theory,3rd ed. Englewood Cliffs, NJ: Prentice-Hall, 1996Google Scholar
  3. 3.
    S. J. Chern and C.Y. Sung, “The Performance of Hybrid Adaptive Beamforming Algo-rithm for Jammers Suppression,” IEEE Trans. Antennas and Propagation, vol. 42, pp. 1223–1232, Sept. 1994CrossRefGoogle Scholar
  4. 4.
    S. J. Chern and C. Y. Chang, “Adaptive Linearly Constrained Inverse QRD-RLS Beam-forming Algorithm for Moving Jammer Suppression, ”IEEE Trans. on Antennas and Propagation, vol. 50, pp. 1138–1150, Aug. 2002CrossRefGoogle Scholar
  5. 5.
    L. S. Resende, J. M. Romano and M.G. Bellanger, “A robust FLS algorithm for LCMV adaptive broad band beamformer,” Proc. IEEE Int. Conf. Acoustic, Speed and Signal pro-cessing, vol. 3, pp. 1826–1829, 1996Google Scholar
  6. 6.
    Z. Tian, K. L. Bell and H. L. Van Trees, “A Recursive Least Squares Implementation for LCMP Beamforming Under Quadratic Constraint,” IEEE Trans. Antennas and Propaga-tion, vol. 49, no. 6, June 2001Google Scholar
  7. 7.
    T. J. Shan and T. Kailath,“Adaptive Beamforming for Coherent Signals and Interference,” IEEE Trans. Signal Processing, vol. ASSP-33, no. 3, June 1985Google Scholar
  8. 8.
    M. Agrawal and S. Prasad,“Robust Adaptive Beamforming for wide-band, Moving, and Coherent Jammers via Uniform Linear Arrays,” IEEE Trans. Antennas and Propagation, vol. 47, no. 8, pp. 1267–1275, Aug. 1999CrossRefGoogle Scholar
  9. 9.
    A. B. Gresham, G. V. Serebryakov and J. F. Bohme, “Constrained Hung–Turner Adaptive Beamforming Algorithm with Additional Robustness to Wideband and Moving Jammers,” IEEE Trans. Antennas and Propagation, vol. 44, pp. 361–366, March 1996CrossRefGoogle Scholar
  10. 10.
    Don H. Johnson and Dan E. Dudgeon, Array Signal Processing Concepts and Techniques, Englewood Cliffs, NJ: Prentice-Hall, 1993MATHGoogle Scholar
  11. 11.
    B. D. Van Veen and K. M. Buckley,“Beamforming: A Versatile Approach to Spatial Filter-ing,” IEEE Acoust, Speech, Signal Processing Mag, vol. 5, pp. 4–24, Apr. 1988Google Scholar
  12. 12.
    G. D. Mandyam, N. Ahmed and M. D. Srinath, “Adaptive Beamforming Based on the Conjugate Gradient Algorithm,”/EEE Trans. on Aerospace and Electronics Systems, vol. 33, no. 1, Jan. 1997Google Scholar
  13. 13.
    G. K. Boray and M. D. Srinath, “Conjugate Gradient Techniques for Adaptive Filtering, ”IEEE Trans. Circuits Systems I, vol. 39, pp. 1–10, Jan. 1992CrossRefGoogle Scholar
  14. 14.
    P. S. Chang and A. N. Willson, Jr.,“Adaptive Spectral Estimation Using the Conjugate Gra-dient Algorithm” Proc. IEEE Int. Conf. Acoustic, Speech, and Signal Processing, Atlanta, pp. 2979–2982, May 1996Google Scholar
  15. 15.
    G. H. Golub and C. F. Van Loan, Matrix Computations, 2–1 ed. Baltimore, MD: Johns Hopkins University Press, 1990Google Scholar
  16. 16.
    P. S. Chang and A. N. Willson Jr., “Analysis of Conjugate Gradient Algorithm for Adap-tive Filtering,” IEEE Trans. Signal Processing, vol. 48, pp. 409–418, Feb. 2000MATHCrossRefGoogle Scholar
  17. 17.
    J. A. Apolinario, Jr., M. L. R. de Campos and C. P. Bernal 0.,“The Constrained Conjugate Gradient Algorithm,” IEEE Signal Processing, vol 7, Dec. 2000Google Scholar
  18. 18.
    L. S. Resende, J. M. Romano and M.G. Bellanger, “A Fast Least-Squares Algorithm for Linearly Constrained Adaptive filtering;’ IEEE Trans. on Signal Processing, vol. 44, no. 5, May 1996Google Scholar
  19. 19.
    M. G. Bellanger, Adaptive Filters and Signal Analysis. New York: Marcel Dekker, 1987Google Scholar
  20. 20.
    S. J. Chern and S. M. Wang,“Adaptive Multiuser Detector for DS-CDMA Over Multipath Fading Channel with Linearly Constrained Constant Modulus Modified Conjugate Gradient Algorithm,” IEEE 2003 International Symposium on Intelligent Signal Processing and Communication Systems, Awaji Island, Japan, pp. 297–302, Dec. 7–10, 2003Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Shiunn-Jang Chern
    • 1
  1. 1.Department of Electrical EngineeringNational Sun Yat-Sen UniversityKaohsiungTaiwan

Personalised recommendations