Chaotic Staggered PRF and Reduced Rank STAP for Airborne Radar
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This paper is a contribution for the suppression of interferences in monostatic airborne radar detection. We propose to consider the projection approximation subspace tracking (PAST) and orthonormal PAST (OPAST) algorithms for the reduction of the rank. Simulation results are presented and the performance of space-time adaptive processing (STAP) is discussed with a comparative study to the principal components (PC) method. Performance curves show that PAST and OPAST do indeed allow good detection of slow moving targets even with low rank covariance matrix.
In order to achieve good detection performance in the case of Doppler ambiguous environment, we propose a novel idea using the rich properties of chaos. It resides in changing the PRF in a chaotic manner. Results show that this solves well the problem of ambiguities while using a reduced rank STAP. Furthermore, we also show using a chaotic staggered PRF, the recursive algorithms give better results than the methods based on eigenvalues decomposition
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A.Nevzat Tarim and Gülay İyibakanlar, Beamforming the Antenna Arrays in the Localizer Unit of Instrument Landing System by Using Genetic Algorithm, International Review of Aerospace Engineering (IREASE) 6-3 (2013), 179-186.
Xiangyang Jin, Xiangyi Guan, Lili Zhao, Hanlin Yang, Ming Pang, Tiefeng Zhang, Spectral Analysis and Independent Component Separation for Aero-Engine Rotor Vibration Signals, International Review of Aerospace Engineering (IREASE) 5-5 (2012), 240-244.
Yılmaz Kalkan, On the Advantages of Frequency-Only MIMO Radar, International Review of Aerospace Engineering (IREASE) 6-5 (2013), 250-255.
J.Ward, Space-Time Adaptive Processing for airborne radar, Technical Report 1015, Lincoln Laboratory MIT (1994).
R.KlemmSpace Time Adaptive Processing Principles and applications, (The Institution of Electrical Engineers, London 1998).
L.E.Brennan, I.S.Reed, Theory of radar, IEEE transactions on Aerospace and Electronics AES-9, N° 2 (1973), 237-252.
A.Haimovich, Eigencanceler: adaptive radar by eigenanalysis methods, IEEE Transactions on Aerospace and Electronic Systems 32-2 (1996), 532–542.
H.Nguyen,Robust Steering Vector Mismatch Techniques forReduced Rank Adaptive Array Signal Processing, Ph.Ddissertation, Dept. Elect. Eng., Virginia Polytechnic Institute and StateUniv., Virginia, USA, 2002.
J.S.Goldstein, I.S.Reed, Theory of partially adaptive radar, IEEE Transactions on Aerospace and Electronics Systems In Proceedings of the IEEE National Radar Conference 33-4(1997), 1309-1325.
S.D. Berger, B.M.Welsh, Selecting a reduced-rank transformation for STAP, a direct form perspective, IEEE Transactions on Aerospace and Electronics Systems 35-2(1999), 722-729.
J.R.Guerci, J.S.Goldstein, I.S.Reed, Optimal and adaptive reduced-rank STAP, IEEE Transactions on Aerospace and Electronics Systems 36-2 (2000), 647-663.
P.G.Richardson, STAP covariance matrix structure and its impact on clutter plus jamming suppression solutions, Electronics Letters 37-2(2001), 118–119.
S.Dib, M.Barkat, J.M.Nicolas, M.Grimes, A Reduced Rank STAP with Change of PRF, Proc. Eusipco (European signal processing conference), September 2007, Poznan, Poland, pp. 95-122, (2007)
E.W.L.Melvin, A STAP Overview, IEEE A & Systems Magazine 19-1(2004), 19-35.
B.Mahafza,Radar signal analysis and processing using matlab, (Taylor & Francis Group, LLC2009).
S.Dib, M.Barkat, J.M.Nicolas, M.Grimes, A Reduced Rank STAP and Staggered PRF for Multiple Target Situations, International Journal on New Computer Architectures and Their Applications (IJNCAA) (2012), 52-69.
S.Dib, M.Barkat, M.Grimes, PAST and OPAST Algorithms for STAP in Monostatic Airborne Radar, Proc. IEEE Conference of INISTA (International Symposium on Innovations in Intelligent SysTems and Applications), Istanbul, Turkey, 177-181, (2011).
S.Dib, M.Barkat, M.Benslama, Iterative Subspace Algorithms and Staggered PRF for Monostatic Airborne Radar, Series B, Signal Processing and Pattern Recognition, AMSE Journal (2014), In press.
R.Klemm, STAP with staggered PRF, 5th International Conference on Radar Systems, Brest, France, pp. 17-21, (1991)
P.Comon, G.H.Golub, Tracking a few extreme singular values and vectors in signal processing, Proc. of the IEEE 78-8(1990), 1327-1343.
B.Yang, Projection Approximation SubspaceTracking, IEEE-T-SP44-1 (1996), 95-107.
K.Abed-Meraim, A.Chkeif, Y.Hua, Fast Orthonormal PAST Algorithm,IEEE Signal Processing Letters, 7 (2000), 60–62.
A.Valizadeh, M.Karimi, Fast Subspace tracking algorithm based on the constrained projection approximation, EURASIP Journal on Advances in Signal Processing (2009), 1-16.
Parker, T.S. and Chua, L.O., Chaos: a tutorial for engineers,Proc. IEEE 75-8 (1987), pp. 982-1008.
Haykin, Chaotic signal processing: New research directions and novel applications, IEEE workshop on SSAP, Victoria, (1992).
Haykin S. and Li, X. B., Detection of signals in chaos, Proc. IEEE 83-1 (1995), 95-122.
Yu, S. and Lu, J., High Order Chua's Circuit and Its FPGA Realization , Proc.IEEE 83-1 (2007), 409-413.
Mital, P. B., KumarU. and Prasad, R. S., Chua’s Circuit – A Universal Paradigm for Generating and Studying Chaos, Journal of Active and Passive Electronic Devices, Vol. 3 (2008), 51–63.
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