Skip to main content
SpringerLink
Log in

Linear Chirp Signal DOA Estimation Using Sparse Time–Frequency Dictionary

  • Published:
International Journal of Wireless Information Networks Aims and scope Submit manuscript

Abstract

This paper is concerned with the estimation of the directions-of-arrival (DOA) of multiple linear chirp signals. We construct a novel time-frequency dictionary based on the properties of chirp signals in the fractional Fourier domain, and a sparse reconstruction algorithm is proposed to achieve high performance. Then, the errors resulting from the off-grid model mismatch is considered, and the dictionary matrix is reformulated into a multiplication of a fixed matrix and a sparse matrix. Further, an iterative alternating approach is proposed to improve the accuracy of the DOA estimates. The proposed algorithm provides better estimation, anti-correlation performances and increased resolution than Multiple Signal Classification (MUSIC) and the time–frequency MUSIC (TF-MUSIC) based on the spatial time–frequency distributions. Simulation results demonstrate the effectiveness of the proposed approach.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. A. Belouchrani and M. G. Amin, Time-frequency MUSIC, IEEE Signal Process. Lett., Vol. 6, No. 5, pp. 109–110, 1999.

    Article  Google Scholar 

  2. H. I. Choi and W. J. Williams, Improved time-frequency representation of multicomponent signals using exponential kernels, IEEE Trans. Acoust. Speech Signal Processing, Vol. 37, pp. 862–871, 1989.

    Article  Google Scholar 

  3. C. Clemente and J. J. Soraghan, Range Doppler and chirp scaling processing of synthetic aperture radar data using the fractional Fourier transform, Signal Processing, IET, Vol. 6, No. 5, pp. 503–510, 2012.

    Article  Google Scholar 

  4. S. A. Elgamel and J. J. Soraghan, Using EMD-FrFT filtering to mitigate very high power interference in chirp tracking radars, IEEE Signal Process. Lett., Vol. 18, No. 4, pp. 263–266, 2011.

    Article  Google Scholar 

  5. D. M. Malioutov, M. Cetin and A. S. Willsky, Sparse signal reconstruction perspective for source localization with sensor arrays, IEEE Trans. Signal Processing, Vol. 53, No. 8, pp. 3010–3022, 2005.

    Article  MathSciNet  Google Scholar 

  6. A. C. Gurbuz, V. Cevher and J. H. McClellan, Bearing estimation via spatial sparsity using compressive sensing, IEEE Trans. Aerospace and Electronic Systems, Vol. 48, No. 2, pp. 1358–1369, 2012.

    Article  Google Scholar 

  7. Y. J. Chi, L. L. Scharf, A. Pezeshki and A. R. Calderbank, Sensitivity to basis mismatch in compressed sensing, IEEE Trans. Signal Processing, Vol. 59, No. 5, pp. 2182–2195, 2011.

    Article  MathSciNet  Google Scholar 

  8. R. Schmidt, Multiple emitter location and signal parameter estimation, IEEE Trans. Antennas and Propagation, Vol. 34, No. 3, pp. 276–280, 1986.

    Article  Google Scholar 

  9. H. M. Ozaktas, M. A. Kutay and D. Mendlovic, Introduction to the fractional fourier transform and its applications, Adv. Imag. Electron. Phys., Vol. 10, No. 6, pp. 239–291, 1999.

    Article  Google Scholar 

  10. L. Qi, R. Tao, S. Y. Zhou, et al., Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform, Sci. China F Inf. Sci., Vol. 47, pp. 184–198, 2004.

    Article  MathSciNet  Google Scholar 

  11. J. Yu, L. Zhang and K. Liu, Coherently distributed wideband LFM source localization, IEEE Signal Process. Lett., Vol. 22, No. 4, pp. 504–508, 2015.

    Article  Google Scholar 

  12. P. Tseng, Convergence of a block coordinate descent method for nondifferentiable minimization, Journal of Optimization Theory and Applications, Vol. 109, No. 3, pp. 475–494, 2001.

    Article  MathSciNet  Google Scholar 

  13. H. Krim and M. Viberg, Two decades of array signal processing research: the parametric approach, IEEE Signal Process. Mag., Vol. 13, No. 4, pp. 67–94, 1996.

    Article  Google Scholar 

  14. P. Stoica and A. Nehorai, Performance study of conditional and unconditional direction-of arrival estimation, IEEE Trans Acoust. Speech Signal Processing., Vol. 38, pp. 1783–1795, 1990.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by in part by the Scientific Research Foundation of Civil Aviation University of China under Grant 2017QD14X and the National Science Foundation of China under Grant 61501322. We thank the anonymous reviewers for providing helpful comments on earlier drafts of the manuscript.

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Civil Aviation University of China, Tianjin, China

    Liang Zhang

  2. Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, USA

    Cheng-Yu Hung

  3. School of Electronic Information Engineering, Tianjin University, Tianjin, China

    Jiexiao Yu & Kaihua Liu

Authors
  1. Liang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cheng-Yu Hung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiexiao Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kaihua Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liang Zhang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, L., Hung, CY., Yu, J. et al. Linear Chirp Signal DOA Estimation Using Sparse Time–Frequency Dictionary. Int J Wireless Inf Networks 27, 568–574 (2020). https://doi.org/10.1007/s10776-020-00489-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10776-020-00489-1

Keywords

Search

Navigation