Skip to main content
SpringerLink
Log in

Improved design of unimodular waveforms for MIMO radar

  • Published:
Multidimensional Systems and Signal Processing Aims and scope Submit manuscript

Abstract

This paper proposes a novel method of unimodular transmitting waveforms design for multiple-input multiple-output (MIMO) radar to strengthen the detection performance in the presence of clutter and white Gaussian noise. An improved iterative algorithm is put forward to maximize the signal-to-clutter-plus-noise ratio (SCNR) under the constant modulus constraint. During iterations, the optimization of unimodular waveforms with filters fixed is a nonconvex fractional quadratically constrained quadratic program problem, which is NP-hard and not able to be solved in polynomial time. An algorithm based on semidefinite programming relaxation combined with bisection and Gaussian randomization is introduced to provide the high-quality suboptimal solutions with a polynomial time computational complexity. The analysis on the approximation bound is given to prove the tightness of the semidefinite programming relaxation and so the correctness of the proposed algorithm. The simulation results show that the improved method is efficient in designing unimodular waveforms for MIMO radar to achieve a better SCNR performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Amaral, P., Bomze, I. M., & Jdice, J. (2010). Copositivity and constrained fractional quadratic problems. Technical Report TR-ISDS 2010-05, University of Vienna.

  • Beck A., Ben-Tal A., Teboulle M. (2005) Finding a global optimal solution for a quadratically constrained fractional quadratic problem with applications to the regularized total least squares. Society for industrial and applied mathematics. Journal on Matrix Analysis Applications 28(2): 425–445

    Article  MathSciNet  Google Scholar 

  • Boyd S., Vandenberghe L. (2004) Convex optimization. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Chen C. Y., Vaidyanathan P. P. (2009) MIMO radar waveform optimization with prior information of the extended target and clutter. IEEE Transactions on Signal Processing 57(9): 3533–3544

    Article  MathSciNet  Google Scholar 

  • Fishler, E., Haimovich, A., Blum, R., Cimini, L., Chizhik, D., & Valenzuela, R. (2004). MIMO radar: An idea whose time has come. In Proceedings of 2004 IEEE International Conference Radar, Philadelphia, PA (pp 71–78).

  • Friedlander B. (2007) Waveform design for MIMO radars. IEEE Transactions on Aerospace Electronic System 43(3): 1227–1238

    Article  Google Scholar 

  • Grant, M., & Boyd, S. (2008). CVX: Matlab software for disciplined convex programming. http://stanford.edu/~boyd/cvx.

  • Haimovich M., Blum R.S., Cimini L.J. Jr. (2008) MIMO radar with widely separated antennas. IEEE Signal Processing Magazine 25(1): 116–129

    Article  Google Scholar 

  • Li J., Stoica P. (2007) MIMO radar with collocated antennas. IEEE Signal Processing Magazine 24(7): 106–114

    Article  Google Scholar 

  • Luo Z. Q., Sidiropoulos N. D., Tseng P., Zhang S. Z. (2007) Approximation bounds for quadratic optimization with homogeneous quadrtic constraints. Society for industrial and applied mathematics. Journal on Optimization 18(1): 1–28

    Article  MathSciNet  MATH  Google Scholar 

  • Luo Z. Q., Ma W. K., So A. M. C., Ye Y. Y., Zhang S. Z. (2010) Semidefinite relaxation of quadratic optimization problems. IEEE Signal Processing Magazine 27(3): 20–34

    Article  Google Scholar 

  • Nemirovski A., Roots C., Terlaky T. (1999) On maximization of quadratic form over intersection of ellipsoids with common center. Mathematical Programming 86: 463–473

    Article  MathSciNet  MATH  Google Scholar 

  • Palomar D. P., Eldar Y. (2010) Convex optimization in signal processing and communications. Cambridge University Press, New York

    MATH  Google Scholar 

  • Pillai, S. U. & Oh, H. S. (2003). Optimum MIMO transmit-receiver design in presence of interference. In Proceedings of ISCAC of International Symposium on Circuits and Systems (pp. IV436–IV439).

  • Zhang J. D., Zhu X. H., Wang H. Q. (2009) Adaptive radar phase-coded waveform design. IET Electronic Letters 45(20): 1052–1053

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing, 210094, People’s Republic of China

    Shanna Zhuang & Xiaohua Zhu

Authors
  1. Shanna Zhuang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaohua Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shanna Zhuang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhuang, S., Zhu, X. Improved design of unimodular waveforms for MIMO radar. Multidim Syst Sign Process 24, 447–456 (2013). https://doi.org/10.1007/s11045-011-0171-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11045-011-0171-2

Keywords

Search

Navigation