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Abstract
Space-time adaptive processing (STAP) is a signal processing technique most commonly used in radar systems where interference is a problem. The radar signal processor is used to remove the unintentional cluttering effects caused by ground reflections and echoes due to sea, desert, forest, etc. and intentional jamming and make the received signal useful. In this paper a new approach to STAP based on subspace projection has been described in detail. According to linear algebra and three dimensional geometry, if we project a range space on to a subspace spanned by linearly independent vectors, we can suppress data which is perpendicular to that subspace. In subspace based technique, the received data is projected on to a subspace which is orthogonal to clutter subspace to remove the clutter. The probability of target detection can be find out in order to analyse the performance of the proposed algorithm. Two existing algorithms, SMI and DPCA are chosen to do the comparison. while plotting the detection Probability against SINR , the results obtained are better for subspace technique than DPCA and SMI. We got the SINR improved for subspace based technique for same detection probability. The effect of subspace rank on SINR was also analysed for understanding the computational load caused by the technique. We also analysed the convergence of the algorithm by taking plots of SINR against range snapshots.
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How to Cite
Baby, E., & Bhargave, D. P. A. A. (2014). Space Time Adaptive Processing for Clutter Suppression in Radar. International Journal of Emerging Trends in Science and Technology, 1(03). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/104
References
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D. Rabideau and A. Steinhardt, “Improved Adaptive Clutter Cancellation through Data-Adaptive Trainingâ€, IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 3 (1999), pp. 879-891
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BARBAROSSA,S., and FARINA,A,:â€Space time frequency processing of synthetic aperture radar signalsâ€,IEEE TRANS. Aerosp.Electron.syst,1994,30,pp 341-358
Zatman, M “Circular array STAPâ€.IEEE Transactions on Aerospace and Electronic Systems,36, 2 (Apr. 2000), 510-517.
Tapan K. Sarkar and RavirajAdve “Space-Time Adaptive Processing Using Circular Arrays†IEEE Antennas and Propagation Magazine, Vol. 43, No. 1, February 2001
pp.138 - 143
T. K. Sarkar, S. Park, J. Koh, and R. A. Schneible, “A deterministic least square approach to adaptive antennas,†Digital Signal Processing— Rev.J., vol. 6, pp. 185–194, 1996.
T. K. Sarkar, H. Waiig, S. Park, R. Adve, J. Koh, Y. Zhang, M.C. Wicks, and R. D. Brown, “A Deterministic Least Squares Approach to Space-Time Adaptive Processing
B. Friedlander, "A Subspace Method for Space Time Adaptive Processing,"IEEE Trans. Sig. Proc. pp. 74-82, Jan. 2005
J. S. Goldstein and I. S. Reed, “Subspace selection for partially adaptive sensor array processingâ€, Aerospace and Electronic Systems, IEEE Transactions on, vol. 33, no. 2, pp. 539–544, 1997
J. Ward, “Space-Time Adaptive Processing for Airborne Radarâ€, Technical Report 1015, MIT Lincoln
Laboratory, Lexington, MA, USA, 1994 (available: http://handle.dtic.mil/100.2/ADA293032)
D. Rabideau and A. Steinhardt, “Improved Adaptive Clutter Cancellation through Data-Adaptive Trainingâ€, IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 3 (1999), pp. 879-891
A. M. Haimovich and Y. Bar-Ness, “An Eigen analysis interference cancellerâ€, Signal Processing, IEEE Transactions on, vol. 39, no. 1,pp. 76–84, 1991.
A. Haimovich, “The Eigen canceller: adaptive radar by Eigen analysis methodsâ€, Aerospace and Electronic Systems, IEEE Transactions on,vol. 32, no. 2, pp. 532–542, 1996.
A. M. Haimovich and M. Berin, “Eigen analysis-based space-time adaptive radar: performance analysisâ€, Aerospace and Electronic Systems,IEEE Transactions on, vol. 33, no. 4, pp. 1170–1179, 1997.
BARBAROSSA,S., and FARINA,A,:â€Space time frequency processing of synthetic aperture radar signalsâ€,IEEE TRANS. Aerosp.Electron.syst,1994,30,pp 341-358
Zatman, M “Circular array STAPâ€.IEEE Transactions on Aerospace and Electronic Systems,36, 2 (Apr. 2000), 510-517.
Tapan K. Sarkar and RavirajAdve “Space-Time Adaptive Processing Using Circular Arrays†IEEE Antennas and Propagation Magazine, Vol. 43, No. 1, February 2001
pp.138 - 143
T. K. Sarkar, S. Park, J. Koh, and R. A. Schneible, “A deterministic least square approach to adaptive antennas,†Digital Signal Processing— Rev.J., vol. 6, pp. 185–194, 1996.
T. K. Sarkar, H. Waiig, S. Park, R. Adve, J. Koh, Y. Zhang, M.C. Wicks, and R. D. Brown, “A Deterministic Least Squares Approach to Space-Time Adaptive Processing
B. Friedlander, "A Subspace Method for Space Time Adaptive Processing,"IEEE Trans. Sig. Proc. pp. 74-82, Jan. 2005
J. S. Goldstein and I. S. Reed, “Subspace selection for partially adaptive sensor array processingâ€, Aerospace and Electronic Systems, IEEE Transactions on, vol. 33, no. 2, pp. 539–544, 1997