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Design of unimodular sequences with small PSL

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Abstract

In this paper, we address the intra-pulse coding for single-input single-output radar systems. As the design metric, we consider the peak sidelobe level (PSL), which is important to be small to avoid masking of the weak targets in the range sidelobes of a strong target. The optimization problem, i.e., minimizing the PSL, is Np-hard in general. The adopted constraint is constant modulus, which is practically important in radar systems, as transmit power amplifiers are typically working in saturation, i.e., transmitting constant amplitude probing signals. The imposed constraint is non-convex that increases the complexity of the problem. By the mathematical manipulation proposed in this paper, we convert the non-convex problem to a convex one and tackle it using semidefinite programming. Simulation and results show the obtained sequences have very small PSL values.

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Notes

  1. Frank sequences are only defined when the code length is perfect square.

References

  1. Alaee-Kerahroodi, M., Aubry, A., De Maio, A., Naghsh, M.M., Modarres-Hashemi, M.: A coordinate-descent framework to design low PSL/ISL sequences. IEEE Trans. Signal Process. 65, 5942–5956 (2017)

    Article  MathSciNet  Google Scholar 

  2. Alaee-Kerahroodi, M., Modarres-Hashemi, M., Naghsh, M.M.: Designing sets of binary sequences for MIMO radar systems. IEEE Trans. Signal Process. 67, 3347–3360 (2019)

    Article  MathSciNet  Google Scholar 

  3. Cilliers, J., Smit, J.: Pulse compression sidelobe reduction by minimization of \(l_{p}\)-norms. IEEE Trans. Aerosp. Electron. Syst. 43, 1238–1247 (2007)

    Article  Google Scholar 

  4. Li, J., Stoica, P., Zheng, X.: Signal synthesis and receiver design for MIMO radar imaging. IEEE Trans. Signal Process. 56, 3959–3968 (2008)

    Article  MathSciNet  Google Scholar 

  5. Stoica, P., He, H., Li, J.: New algorithms for designing unimodular sequences with good correlation properties. IEEE Trans. Signal Process. 57, 1415–1425 (2009)

    Article  MathSciNet  Google Scholar 

  6. He, H., Stoica, P., Li, J.: Designing unimodular sequence sets with good correlations; including an application to MIMO radar. IEEE Trans. Signal Process. 57, 4391–4405 (2009)

    Article  MathSciNet  Google Scholar 

  7. Song, J., Babu, P., Palomar, D.: Optimization methods for designing sequences with low autocorrelation sidelobes. IEEE Trans. Signal Process. 63, 3998–4009 (2015)

    Article  MathSciNet  Google Scholar 

  8. Song, J., Babu, P., Palomar, D.P.: Sequence design to minimize the weighted integrated and peak sidelobe levels. IEEE Trans. Signal Process. 64, 2051–2064 (2016)

    Article  MathSciNet  Google Scholar 

  9. Song, J., Babu, P., Palomar, D.P.: Sequence set design with good correlation properties via majorization–minimization. IEEE Trans. Signal Process. 64, 2866–2879 (2016)

    Article  MathSciNet  Google Scholar 

  10. Song, J., Babu, P., Palomar, D.P.: Sequence design to minimize the peak sidelobe level. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3896–3900 (2016)

  11. Zhao, L., Song, J., Babu, P., Palomar, D.P.: A unified framework for low autocorrelation sequence design via majorization–minimization. IEEE Trans. Signal Process. 65, 438–453 (2017)

    Article  MathSciNet  Google Scholar 

  12. Alaee-Kerahroodi, M., Modarres-Hashemi, M., Naghsh, M.M., Shankar, B., Ottersten, B.: Binary sequences set with small ISL for MIMO radar systems. In: 2018 26th European Signal Processing Conference (EUSIPCO), pp. 2395–2399 (2018)

  13. Alaee-Kerahroodi, M., Sedighi, S., Shankar M.R.B., Ottersten, B.: Designing (in)finite-alphabet sequences via shaping the radar ambiguity function. In: ICASSP 2019—2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4295–4299 (2019)

  14. Alaee-Kerahroodi, M., Bhavani Shankar, M.R., Mishra, K.V., Ottersten, B.: Meeting the lower bound on designing set of unimodular sequences with small aperiodic/periodic ISL. In: 2019 20th International Radar Symposium (IRS), pp. 1–13 (2019)

  15. Alaee-Kerahroodi, M., Mishra, K.V., Bhavani Shankar, M.R., Ottersten, B.: Discrete-phase sequence design for coexistence of MIMO radar and MIMO communications. In: 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 1–5 (2019)

  16. De Maio, A., Huang, Y., Piezzo, M., Zhang, S., Farina, A.: Design of radar receive filters optimized according to \(l_{p}\)-norm based criteria. IEEE Trans. Signal Process. 59, 4023–4029 (2011)

    Article  MathSciNet  Google Scholar 

  17. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)

    Book  Google Scholar 

  18. Petersen, K.B., Pedersen, M.S., Larsen, J., Strimmer, K., Christiansen, L., Hansen, K., He, L., Thibaut, L., BarÃo, M., Hattinger, S., Sima, V., The, W.: The matrix cookbook. Technical report (2006)

  19. Chen, X., Qi, H., Qi, L., Teo, K.-L.: Smooth convex approximation to the maximum eigenvalue function. J. Glob. Optim. 30(2), 253–270 (2004)

    Article  MathSciNet  Google Scholar 

  20. Aubry, A., De Maio, A., Zappone, A., Razaviyayn, M., Luo, Z.: A new sequential optimization procedure and its applications to resource allocation for wireless systems. IEEE Trans. Signal Process. 66, 6518–6533 (2018)

    Article  MathSciNet  Google Scholar 

  21. Razaviyayn, M., Hong, M., Luo, Z.-Q.: A unified convergence analysis of block successive minimization methods for nonsmooth optimization. SIAM J. Optim. 23, 1126–1153 (2013)

    Article  MathSciNet  Google Scholar 

  22. Hunter, D.R., Lange, K.: A tutorial on MM algorithms. Am. Stat. 58(1), 30–37 (2004)

    Article  MathSciNet  Google Scholar 

  23. Stoica, P., Selen, Y.: Cyclic minimizers, majorization techniques, and the expectation–maximization algorithm: a refresher. IEEE Signal Process. Mag. 21, 112–114 (2004)

    Article  Google Scholar 

  24. Mohar, B., Poljak, S.: Eigenvalues in combinatorial optimization. In: Combinatorial and Graph-Theoretical Problems in Linear Algebra, pp. 107–151. Springer (1993)

  25. Laurent, M., Vallentin, F.: Semidefinite optimization. Lecture Notes. (2012). http://page.mi.fu-berlin.de/fmario/sdp/laurentv.pdf. Accessed 28 Mar 2012

  26. De Maio, A., De Nicola, S., Huang, Y., Zhang, S., Farina, A.: Code design to optimize radar detection performance under accuracy and similarity constraints. IEEE Trans. Signal Process. 56, 5618–5629 (2008)

    Article  MathSciNet  Google Scholar 

  27. Aubry, A., DeMaio, A., Farina, A., Wicks, M.: Knowledge-aided (potentially cognitive) transmit signal and receive filter design in signal-dependent clutter. IEEE Trans. Aerosp. Electron. Syst. 49, 93–117 (2013)

    Article  Google Scholar 

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Correspondence to M. Bagher Alaie.

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Alaie, M.B., Olamaei, S.A. Design of unimodular sequences with small PSL. SIViP 14, 799–806 (2020). https://doi.org/10.1007/s11760-019-01610-5

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