LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Languages: English
Types: Article
Subjects: 1711, 2208
In this paper, we propose a reduced-rank space-time adaptive processing (STAP) technique for airborne phased array radar applications. The proposed STAP method performs dimensionality reduction by using a reduced-rank switched joint interpolation, decimation and filtering algorithm (RR-SJIDF). In this scheme, a multiple-processing-branch (MPB) framework, which contains a set of jointly optimized interpolation, decimation and filtering units, is proposed to adaptively process the observations and suppress jammers and clutter. The output is switched to the branch with the best performance according to the minimum variance criterion. In order to design the decimation unit, we present an optimal decimation scheme and a low-complexity decimation scheme. We also develop two adaptive implementations for the proposed scheme, one based on a recursive least squares (RLS) algorithm and the other on a constrained conjugate gradient (CCG) algorithm. The proposed adaptive algorithms are tested with simulated radar data. The simulation results show that the proposed RR-SJIDF STAP schemes with both the RLS and the CCG algorithms converge at a very fast speed and provide a considerable SINR improvement over the state-of-the-art reduced-rank schemes.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] L. E. Brennan and I. S. Reed, “Theory of adaptive radar”, IEEE Trans.
    • Aero. Elec. Syst., vol. AES-9, no. 2, pp. 237-252, 1973.
    • [2] I. S. Reed, J. D. Mallett, and L. E. Brennan, “Rapid convergence rate in adaptive arrays”, IEEE Trans. Aero. Elec. Syst., vol. AES-10, no. 6, pp.
    • [3] E. J. Kelly, “An adaptive detection algorithm”, IEEE Trans. Aero. Elec.
    • Syst., vol. AES-22, no. 2, pp. 115-127, 1986.
    • [4] A. M. Haimovich and Y. Bar-Ness, “An eigenanalysis interference canceler”, IEEE Trans. Sig. Process., vol. 39, no. 1, pp. 76-84, 1991.
    • e adaptive matched filter detector”, IEEE Trans. Aero. Elec. Syst., vol. 28, [5] F. C. Robey, D. R. Fuhrmann, E. J. Kelly, and R. Nitzberg, “A CFAR no. 1, pp. 208-216, Jan 1992.
    • v [6] J. Ward, “Space-time adaptive processing for airborne radar,”, Tech. Rep.
    • Full−Rank−RLS 1015, MIT Lincoln lab., Lexington, MA, Dec. 1994.
    • AVF i methods”, IEEE Trans. Aero. Elec. Syst., vol. 32, no. 2, pp. 532-542, JDL−RLS [7] A. Haimovich, “The eigencanceler: adaptive radar by eigenanalysis MSWF−RLS e 1996.
    • RR−SJIDF−CCG [8] J. S. Goldstein and I. S. Reed, “Reduced-rank adaptive filtering”, IEEE RORpt−imSaJIlDF−RLS w[9] JT.raSn.sG. oSlidgs.tePirnoacnesds.I,. vSo. lR.e4e5d,,n“oT. h2e,opryp.o4f9p2a-r4ti9a6ll,y1a9d9a7p.tive radar”, IEEE 100 150 Trans. Aero. Elec. Syst., vol. 33, no. 4, pp. 1309-1325, 1997.
    • [10] Y.-L. Gau and I.S. Reed, “An improved reduced-rank CFAR space-time O8,pp. no. 2139-2146, Aug 1998.
    • adaptive radar detection algorithm”, IEEE Trans. Sig. Process., vol. 46, [11] I. S. Reed, Y. L. Gau, and T. K. Truong, “CFAR detection and estimation for STAP radar”, IEEE Trans. Aero. Elec. Syst., vol. 34, no. 3, pp. 722- 735, 19n98.
    • [12] J. S. Goldstein, I. S. Reed, and P. A. Zulch, “Multistage partially adaptive 35, no. 2, ppl.645-661, 1999.
    • [13] J. R. Guerci, yJ.S. Goldstein, and I. S. Reed, “Optimal and adaptive reduced-rank STAP”, IEEE Trans. Aero. Elec. Syst., vol. 36, no. 2, pp.
    • [14] R. Klemm, Principle of space-time adaptive processing, IEE Press, Bodmin, UK, 2002.
    • [15] W. L. Melvin, “A STAP overview”, IEEE Aero. .Elec. Syst. Mag., vol.
    • 19, no. 1, pp. 19-35, 2004.
    • [16] S. Haykin, Adaptive Filter Theory, NJ: Prentice-Hall, 4th, ed2002.
    • [17] J. S. Goldstein and I. S. Reed, “Subspace selection for partially adaptive sensor array processing”, IEEE Trans. Aero. Elec. Syst., vol. 33, no. 2, pp. 539-544, 1997.
    • [18] J. S. Goldstein, I. S. Reed, and L. L. Scharf, “A multistage representation of the wiener filter based on orthogonal projections”, IEEE Trans. Inf.
    • Theory, vol. 44, no. 7, pp. 2943-2959, 1998.
    • [19] D. A. Pados and S. N. Batalama, “Joint space-time auxiliary-vector filtering for DS/CDMA systems with antenna arrays”, IEEE Trans.
    • Commun., vol. 47, no. 9, pp. 1406-1415, 1999.
    • [20] D. A. Pados and G. N. Karystinos, “An iterative algorithm for the computation of the MVDR filter”, IEEE Trans. Sig. Process.], vol. 49, no. 2, pp. 290-300, Feb 2001.
    • [21] D. A. Pados, G. N. Karystinos, S. N. Batalama, and J. D. Matyjas, “Short-data-record adaptive detection”, 2007 IEEE Radar Conf., pp. 357- 361, 17-20 April 2007.
    • [22] H. Wang, and L. Cai, “On adaptive spatial-temporal processing for airborne surveillance radar systems”, IEEE Trans. Aero. Elec. Syst., vol.
    • 30, no. 3, 660670, 1994.
    • [23] R. S. Adve, T. B. Hale, and M. C. Wicks, “Practical joint domain localised adaptive processing in homogeneous and nonhomogeneous environments. Part 1: Homogeneous environments.”, IEE Proceedings Radar, Sonar and Navigation, vol. 147, no. 2, 5765, 2000.
    • [24] R. S. Adve, T. B. Hale, and M. C. Wicks, “Practical joint domain localised adaptive processing in homogeneous and nonhomogeneous environments. Part 2: Nonhomogeneous environments.”, IEE Proceedings Radar, Sonar and Navigation, vol. 147, no. 2, 6674, 2000.
    • [25] R. C. de Lamare and R. Sampaio-Neto, “Reduced-rank adaptive filtering based on joint iterative optimization of adaptive filters”, IEEE Sig. Proc.
    • Lett., vol. 14, no. 12, pp. 980-983, 2007.
    • [26] R. Fa, R. C. de Lamare, and D. Zanatta-Filho, “Reduced-rank STAP algorithm for adaptive radar based on joint iterative optimization of adaptive filters”, in Conf. Record of the Fourty-Second Asilomar Conf.
    • Sig. Syst. Comp., 2008.
    • [27] R. C. de Lamare and R. Sampaio-Neto, “Adaptive reduced-rank mmse parameter estimation based on an adaptive diversity-combined decimation and interpolation scheme”, in Proc. IEEE Int. Conf. Acous. Speech Sig.
    • Process., 15-20 April 2007, vol. 3, pp. III-1317-III-1320.
    • [28] R. C. de Lamare, and R. Sampaio-Neto, “Adaptive reduced-rank filtering”, IEEE Trans. Sig. Process. , vol.57, no.7, pp.2503-2514, July 2009 o
    • [29] S. Applebaum and D. Chapman, “Adaptive arrays with main beam 1976. r constraints”, IEEE Trans. on Ant. Prop., vol. 24, no. 5, pp. 650-662,
    • [30] G. H. Golub and C. F. van Loan, Matrix Computations, Wiley, 2002.
    • [31] L. S. Resende, J. M. T. Romano, and M. G. Bellanger, “A fast leastSig. Process., vol. 44, no. 5, pp. 1168-1174, 1996.
    • [32] Jr. Apolinario, J. A., M. L. R. De Campos, and C. P. Bernal O, “The 7, no. 12, pp. 351-354, 2000.
    • [33] P. S. Chang and Jr. A. N. Willson, “Analysis of conjugvategradient algorithms for adaptive filtering”, IEEE Trans. Sig. Process., vol. 48, no.
    • [34] M. E. Weippert, J. D. Hiemstra, J. S. Goldstein, and M. D. Zoiltowski, 2, pp. 409-418, Feb. 2000.
    • “Insights from the relationship between the multistage wiener efilter and the method of conjugate gradients”, in Proc. Sensor Array and Multichannel Signal Processing Workshop, 4-6 Aug. 2002, pp. 388-392w.
    • [35] L. L. Scharf, E. K. P. Chong, M. D. Zoltowski, J. S. Goldstein, and I. S.
    • Reed, “Subspace expansion and the equivalence of conjugate direction and multistage wiener filters”, IEEE Trans. Sig. Process., vol. 56, no. 10, pp. 5013-5019, Oct. 2008.
    • [36] L. Wang and R. C. de Lamare, “Constrained adaptive filtering algorithms based on conjugate gradient techniques for beamforming,” Submitted to IET Signal Processing .
    • [37] H. L. Van Trees, Optimum Array Processing, Wiley, New York, 2002.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article