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2018-03-21

Research on Space-Time Adaptive Processing with Respect to the Signal Powers

By Wei Wang, Lin Zou, and Xuegang Wang
Progress In Electromagnetics Research C, Vol. 82, 99-107, 2018
doi:10.2528/PIERC18011401

Abstract

Diverse array processing methods with higher order statistics (HOS) have been developed in the last three decades. One of the main interests in using HOS relies on the increase of effective aperture and the number of sensors of the considered array. In this work, we further exploit space-time adaptive processing (STAP) using HOS based on the phased array radar with uniform linear array (ULA). We implement STAP with respect to signal powers instead of with respect to signal amplitudes as the convention. The purpose of this paper is to provide some important insights into the STAP with respect to signal powers (SP-STAP), such as the output response, output signal-to-interference-plus-noise ratio (SINR), minimum detectable velocity (MDV) performance and effect ofinternal clutter motion (ICM). Compared with the conventional STAP under the condition of the same number of array elements and transmitting pulses, the simulation results show that SP-STAP can gain narrower target main beam, lower side-lobe levels, better MDV performance and less deleterious effect of ICM.

Citation


Wei Wang, Lin Zou, and Xuegang Wang, "Research on Space-Time Adaptive Processing with Respect to the Signal Powers," Progress In Electromagnetics Research C, Vol. 82, 99-107, 2018.
doi:10.2528/PIERC18011401
http://jpier.org/PIERC/pier.php?paper=18011401

References


    1. Melvin, W. L., "A stap overview," IEEE Aerospace and Electronic Systems Magazine, Vol. 19, No. 1, 9-35, Jan. 2004.
    doi:10.1109/MAES.2004.1263229

    2. Klemm, R., "Principles of space-time adaptive processing,", The Institution of Engineering and Technology, London, UK, 2006.

    3. Guerci, J. R., Space-time Adaptive Processing for Radar, Artech House, Boston, USA, 2003.

    4. Li, X. M., D. Z. Feng, H. W. Liu, and D. Luo, "Dimension-reduced space-time adaptive clutter suppression algorithm based on lower-rank approximation to weight matrix in airborne radar," IEEE Transactions on Aerospace and Electronic Systems, Vol. 50, No. 1, 53-69, Jan. 2014.
    doi:10.1109/TAES.2013.080153

    5. Liu, H. W., et al., "A novel STAP algorithm for airborne MIMO radar based on temporally correlated multiple sparse Bayesian learning," Mathematical Problems in Engineering, 2016.

    6. Chen, C. Y. and P. P. Vaidyanathan, "MIMO radar space-time adaptive processing using prolate spheroidal wave functions," IEEE Trans. Signal Process., Vol. 56, No. 2, 623-635, Feb. 2008.
    doi:10.1109/TSP.2007.907917

    7. Leatherwood, D. A., W. L. Melvin, and R. Acree, "Configuring a sparse aperture antenna for spaceborne MTI radar," IEEE Radar Conference, 139-146, Alabama, USA, May 2003.

    8. Morabito, A. F., A. R. Lagana, and T. Isernia, "Isophoric array antennas with a low number of control points: A `size tapered’ solution," Progress In Electromagnetics Research Letters, Vol. 36, 121-131, 2013.
    doi:10.2528/PIERL12092705

    9. Tang, B., X. Yang, H. Wu, and W. Peng, "Research on clutter spectra and STAP for sparse antenna arrays," International Conference on Communications, Circuits and Systems (ICCCAS), Vol. 1, 280-283, Chengdu, China, Nov. 2013.

    10. Mendel, J. M., "Tutorial on higher-order statistics (spectra) in signal processing and system theory: Theoretical results and some applications," Proceedings of the IEEE, Vol. 79, No. 3, 278-305, Mar. 1991.
    doi:10.1109/5.75086

    11. Cardoso, J. F. and E. Moulines, "Asymptotic performance analysis ofdirection finding algorithms based on fourth order cumulants," IEEE Trans. Signal Process., Vol. 43, No. 1, 214-224, Jan. 1995.
    doi:10.1109/78.365301

    12. Gonen, E. and J. M. Mendel, "Applications of cumulants to array processing --- Part VI: Polarization and direction of arrival estimation with minimally constrained arrays," IEEE Trans. Signal Process., Vol. 47, No. 9, 2589-2592, Sep. 1999.
    doi:10.1109/78.782216

    13. De Lathauwer, L., B. De Moor, and J. Vandewalle, "ICA techniques formore sources than sensors," Proc. Workshop Higher Order Statistics, Caesara, Israel, Jun. 1999.

    14. Ferreol, A., L. Albera, and P. Chevalier, "Fourth order blind identification of under determined mixtures of sources (FOBIUM)," Proc. ICASSP, 41-44, Hong Kong, Apr. 2003.

    15. Albera, L., A. Ferreol, P. Comon, and P. Chevalier, "Blind identification of overcomplete mixtures of sources (BIOME)," Linear Algebra and Its Applications, Vol. 391, 3-30, Nov. 2004.

    16. Chevalier, P., A. Ferreol, and L. Albera, "High resolution direction finding from higher order statistics: The 2q-MUSIC algorithm," IEEE Trans. Signal Process., Vol. 54, No. 8, 2986-2997, Aug. 2006.
    doi:10.1109/TSP.2006.877661

    17. Birot, G., L. Albera, and P. Chevalier, "Sequential high-resolution direction finding from higher order statistics," IEEE Trans. Signal Process., Vol. 58, No. 8, 4144-4155, Aug. 2010.
    doi:10.1109/TSP.2010.2049569

    18. Wang, F., X. Cui, and M. Lu, "Direction finding using higher order statistics without redundancy," IEEE Signal Processing Letters, Vol. 20, No. 5, 495-498, May 2013.
    doi:10.1109/LSP.2013.2252010

    19. Dogan, M. C. and J. M. Mendel, "Applications of cumulants to array processing --- Part I: Aperture extension and array calibration," IEEE Trans. Signal Process., Vol. 43, No. 5, 1200-1216, May 1995.
    doi:10.1109/78.382404

    20. Chevalier, P. and A. Ferreol, "On the virtual array concept for the fourthorder direction finding problem," IEEE Trans. Signal Process., Vol. 47, No. 9, 2592-2595, Sep. 1999.
    doi:10.1109/78.782217

    21. Chevalier, P., L. Albera, A. Ferreol, and P. Comon, "On the virtual array concept for higher order array processing," IEEE Trans. Signal Process., Vol. 53, No. 4, 1254-1271, Apr. 2005.
    doi:10.1109/TSP.2005.843703

    22. Pal, P. and P. P. Vaidyanathan, "Nested arrays: A novel approach to array processing with enhanced degrees of freedom," IEEE Trans. Signal Process., Vol. 58, No. 8, 4167-4181, Aug. 2010.
    doi:10.1109/TSP.2010.2049264

    23. Vouras, P., "Fully adaptive space-time processing on nested arrays," IEEE Radar Conference, 0858-0863, Virginia, USA, May 2015.

    24. Morabito, A. F., A. R. Lagana, G. Sorbello, and T. Isernia, "Mask-constrained power synthesis of maximally sparse linear arrays through a compressive-sensing-driven strategy," Journal of Electromagnetic Waves and Applications, Vol. 29, No. 10, 1384-1396, Oct. 2015.
    doi:10.1080/09205071.2015.1046561