[en] In this paper, we aim at designing a set of binary sequences with good aperiodic auto- and crosscorrelation properties for Multiple-Input-Multiple-Output (MIMO) radar systems. We show such a set of sequences can be obtained by minimizing the Integrated Side Lobe (ISL) with the binary requirement imposed as a design constraint. By using the block coordinate descent (BCD) framework, we propose an efficient monotonic algorithm based on Fast Fourier Transform (FFT), to minimize the objective function which is non-convex and NP-hard in general. Simulation results illustrate that the ISL of designed binary set of sequences is the neighborhood of the Welch bound, Indicating its superior performance.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
Alaee-Kerahroodi, Mohammad
Modarres-Hashemi, Mahmoud
Naghsh, Mohammad Mahdi Naghsh
SHANKAR, Bhavani ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
OTTERSTEN, Björn ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Binary Sequences set with small ISL for MIMO radar systems
Date de publication/diffusion :
2018
Nom de la manifestation :
2018 26th European Signal Processing Conference (EUSIPCO)
Date de la manifestation :
3-09-2018 to 7-09-2018
Manifestation à portée :
International
Titre de l'ouvrage principal :
2018 26th European Signal Processing Conference (EUSIPCO)
H. He, J. Li, and P. Stoica, Waveform Design for Active Sensing Systems. Cambridge University Press, 2012.
H. He, P. Stoica, and J. Li, “Designing unimodular sequence sets with good correlations; including an application to MIMO radar,” IEEE Transactions on Signal Processing, vol. 57, pp. 4391-4405, Nov 2009.
J. Li and P. Stoica, MIMO Radar Diversity Means Superiority, pp. 594-. Wiley-IEEE Press, 2009.
A. Hassanien and S. A. Vorobyov, “Phased-MIMO radar: A tradeoff between phased-array and MIMO radars,” IEEE Transactions on Signal Processing, vol. 58, pp. 3137-3151, June 2010.
M. M. Naghsh, M. Modarres-Hashemi, M. Alaee-Kerahroodi, and E. H. M. Alian, “An information theoretic approach to robust constrained code design for MIMO radars,” IEEE Transactions on Signal Processing, vol. 65, pp. 3647-3661, July 2017.
D. J. Rabideau, “MIMO radar waveforms and cancellation ratio,” IEEE Transactions on Aerospace and Electronic Systems, vol. 48, pp. 1167-1178, APRIL 2012.
B. Shtarkalev and B. Mulgrew, “Effects of FDMA/TDMA orthogonality on the gaussian pulse train MIMO ambiguity function,” IEEE Signal Processing Letters, vol. 22, pp. 153-157, Feb 2015.
K. W. Forsythe and D. W. Bliss, “MIMO radar waveform constraints for GMTI,” IEEE Journal of Selected Topics in Signal Processing, vol. 4, pp. 21-32, Feb 2010.
D. J. Rabideau, “Doppler-offset waveforms for MIMO radar,” in 2011 IEEE RadarCon (RADAR), pp. 965-970, May 2011.
A. Zwanetski and H. Rohling, “Continuous wave MIMO radar based on time division multiplexing,” in 2012 13th International Radar Symposium, pp. 119-121, May 2012.
H. Ganapathy, D. A. Pados, and G. N. Karystinos, “New bounds and optimal binary signature sets - part II: Aperiodic total squared correlation,” IEEE Transactions on Communications, vol. 59, pp. 1411-1420, May 2011.
M. Soltanalian, M. M. Naghsh, and P. Stoica, “On meeting the peak correlation bounds,” IEEE Transactions on Signal Processing, vol. 62, pp. 1210-1220, March 2014.
H. Sun, F. Brigui, and M. Lesturgie, “Analysis and comparison of MIMO radar waveforms,” in 2014 International Radar Conference, pp. 1-6, Oct 2014.
B. M. Popovic, N. Suehiro, and P. Z. Fan, “Orthogonal sets of quadriphase sequences with good correlation properties,” IEEE Transactions on Information Theory, vol. 48, pp. 956-959, Apr 2002.
J. Haboba, R. Rovatti, and G. Setti, “Integrated sidelobe level of sets of rotated legendre sequences,” in 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2632-2635, May 2011.
L. Zhao, J. Song, P. Babu, and D. P. Palomar, “A unified framework for low autocorrelation sequence design via Majorization-Minimization,” IEEE Transactions on Signal Processing, vol. 65, pp. 438-453, Jan 2017.
I. A. Arriaga-Trejo, A. G. Orozco-Lugo, and J. Flores-Troncoso, “Design of unimodular sequences with good autocorrelation and good complementary autocorrelation properties,” IEEE Signal Processing Letters, vol. 24, pp. 1153-1157, Aug 2017.
Y. Li and S. A. Vorobyov, “Fast algorithms for designing unimodular waveform(s) with good correlation properties,” IEEE Transactions on Signal Processing, vol. 66, pp. 1197-1212, March 2018.
L. Wu, P. Babu, and D. P. Palomar, “Transmit waveform/receive filter design for MIMO radar with multiple waveform constraints,” IEEE Transactions on Signal Processing, vol. 66, pp. 1526-1540, March 2018.
M. Alaee-Kerahroodi, A. Aubry, A. De Maio, M. M. Naghsh, and M. Modarres-Hashemi, “A coordinate-descent framework to design low PSL/ISL sequences,” IEEE Transactions on Signal Processing, vol. 65, pp. 5942-5956, Nov 2017.
M. Alaee-Kerahroodi, A. Aubry, A. De Maio, M. M. Naghsh, and M. Modarres-Hashemi, “Design of binary sequences with low PSL/ISL,” in 2017 25th European Signal Processing Conference (EUSIPCO), pp. 2211-2215, Aug 2017.
M. Nasrabadi and M. Bastani, A Survey on the Design of Binary Pulse Compression Codes with Low Autocorrelation. INTECH Open Access Publisher, 2010.
M. Skolnik, Radar Handbook, Third Edition. Electronics electrical engineering, McGraw-Hill Education, 2008.
L. Welch, “Lower bounds on the maximum cross correlation of signals (corresp.),” IEEE Transactions on Information Theory, vol. 20, pp. 397-399, May 1974.
J. Song, P. Babu, and D. P. Palomar, “Sequence set design with good correlation properties via majorization-minimization,” IEEE Transactions on Signal Processing, vol. 64, pp. 2866-2879, June 2016.
P. Stoica, H. He, and J. Li, “New algorithms for designing unimodular sequences with good correlation properties,” IEEE Transactions on Signal Processing, vol. 57, pp. 1415-1425, Apr 2009.
Y. Xu and W. Yin, “A block coordinate descent method for regularized multiconvex optimization with applications to non-negative tensor factorization and completion,” SIAM Journal on imaging sciences, vol. 6, no. 3, pp. 1758-1789, 2013.
