Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Reduced-Dimensional Block Sparse Angle Estimation for Bistatic MIMO Radar with Unknown Mutual Coupling

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In this paper, we suggest an efficient algorithm for joint direction-of-arrival (DOA) and direction-of-departure (DOD) estimation in bistatic multiple-input multiple-output (MIMO) radar with unknown mutual coupling. Based on the inherent structure of mutual coupling matrix of MIMO radar array, we firstly extract the data without mutual coupling effects from the outputs of the matched filters. Then, the signal model is transformed by Kronecker product based transformation to realize the block sparse representation of DOD and DOA respectively. This avoids the need for two-dimensional grid dividing in the spatial domain, resulting in a significant reduction in computational complexity. Moreover, considering scenarios involving grid mismatch, off-grid vector is introduced into the block sparse model respectively. Finally, an additional process is performed to pair the DOD and DOA estimates. Simulation results demonstrate the superiority of the proposed algorithm over several existing methods.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Data Availibility

My manuscript has no associated data.

References

  1. Fishler, E., Haimovich, A., Blum, R., Chizhik, D., Cimini, L., & Valenzuela,R. (2004.) “MIMO radar: An idea whose time has come,” in Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509), pp. 71–78.

  2. Zheng, W., Zhang, X., & Shi, J. (2017). Sparse extension array geometry for DOA estimation with nested MIMO radar. IEEE Access, 5(6), 9580–9586.

    Article  Google Scholar 

  3. Fishler, E., Haimovich, A., Blum, R., Cimini, R., Chizhik, D., & Valenzuela, R. (2004). “Performance of MIMO radar systems: advantages of angular diversity,” in Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004., vol. 1, pp. 305–309 .

  4. Haimovich, A. M., Blum, R. S., & Cimini, L. J. (2008). MIMO radar with widely separated antennas. IEEE signal processing magazine, 25(1), 116–129.

    Article  Google Scholar 

  5. Jian, L., & Stoica, P. (2007). MIMO radar with colocated antennas. IEEE signal processing magazine, 24(5), 106–114.

    Article  Google Scholar 

  6. Krim, H., & Viberg, M. (1996). Two decades of array signal processing research: The parametric approach. IEEE signal processing magazine, 13, 67–94.

    Article  Google Scholar 

  7. Zheng, Z., Huang, Y., Wang, W.-Q., & So, H. C. (2021). Augmented covariance matrix reconstruction for DOA estimation using difference coarray. IEEE Transactions on Signal Processing, 69, 5345–5358.

    Article  MathSciNet  Google Scholar 

  8. Ponnusamy, P., Subramaniam, K., & Chintagunta, S. (2019). Computationally efficient method for joint DOD and DOA estimation of coherent targets in MIMO radar. Signal Processing, 165(12), 262–267.

    Article  Google Scholar 

  9. Wang, Y., & Liu, Z. (2015). Joint DOD and DOA estimation using 2-D unitary esprit for bistatic MIMO radar. IET International Radar Conference, 2015, 1–6.

    Google Scholar 

  10. Zhang, X., Xu, L., Xu, L., & Xu, D. (2010). Direction of departure DOD and direction of arrival DOA estimation in MIMO radar with reduced-dimension music. IEEE Communication Letter, 14(12), 1161–1163.

    Article  Google Scholar 

  11. Xu, B., Zhao, Y., Cheng, Z., & Li, H. (2017). A novel unitary PARAFAC method for DOD and DOA estimation in bistatic MIMO radar. Signal Processing, 138(9), 273–279.

    Article  Google Scholar 

  12. Zheng, Z., Guo, N., & Wang, W. (2022). Angle Estimation for Bistatic MIMO Radar Using One-Bit Sampling Via Atomic Norm Minimization. IEEE Transactions on Aerospace and Electronic Systems, 58(6), 5815–5822.

    Article  Google Scholar 

  13. Wen, F., Shi, J., & Zhang, Z. (2020). Joint 2D-DOD, 2D-DOA, and Polarization Angles Estimation for Bistatic EMVS-MIMO Radar via PARAFAC Analysis. IEEE Transactions on Vehicular Technology, 69(2), 1626–1638.

    Article  Google Scholar 

  14. Xie, Q., Pan, X., & Zhao, F. (2023). Joint 2D-DOD and 2D-DOA Estimation in Bistatic MIMO Radar via Tensor Ring Decomposition. IEEE Signal Processing Letter, 30, 1507–1511.

    Article  Google Scholar 

  15. Liu, X., & Liao, G. (2012). Direction finding and mutual coupling estimation for bistatic MIMO radar. Signal Processing, 92(2), 517–522.

    Article  Google Scholar 

  16. Zheng, Z., Zhang, J., & Zhang, J. (2012). Joint DOD and DOA estimation of bistatic MIMO radar in the presence of unknown mutual coupling. Signal Processing, 92(12), 3039–3048.

    Article  Google Scholar 

  17. Wen, F., Xiong, X., & Zhang, Z. (2017). Angle and mutual coupling estimation in bistatic MIMO radar based on parafac decomposition. Digital Signal Processing, 65, 1–10.

    Article  MathSciNet  Google Scholar 

  18. Wen, F., Zhang, Z., Wang, K., Sheng, G., & Zhang, G. (2018). Angle estimation and mutual coupling self-calibration for ula-based bistatic MIMO radar. Signal Processing, 144, 61–67.

    Article  Google Scholar 

  19. Baidoo, E., Hu, J., Bao, Z., & Li, W. (2022). Dynamic subspace angle estimation method for bistatic MIMO radar with system imperfections. Digital Signal Processing, 122, 103331.

    Article  Google Scholar 

  20. Dai, J., Zhao, D., & Ji, X. (2012). A sparse representation method for DOA estimation with unknown mutual coupling. IEEE Antennas and Wireless Propagation Letters, 11, 1210–1213.

    Article  Google Scholar 

  21. Wang, Q., Dou, T., Chen, H., Yan, W., & Liu, W. (2017). Effective block sparse representation algorithm for DOA estimation with unknown mutual coupling. IEEE Communication Letter, 21(12), 2622–2625.

    Article  Google Scholar 

  22. Wang, X., Meng, D., Huang, M., & Wan, L. (2019). Reweighted regularized sparse recovery for DOA estimation with unknown mutual coupling. IEEE Communication Letter, 23(2), 290–293.

    Article  Google Scholar 

  23. Zhang, X., Jiang, T., Li, Y., & Zakharov, Y. (2019). A novel block sparse reconstruction method for DOA estimation with unknown mutual coupling. IEEE Communication Letter, 23(10), 1845–1848.

    Article  Google Scholar 

  24. Tang, W.-G., Jiang, H., & Zhang, Q. (2022). Off-grid DOA estimation with mutual coupling via block log-sum minimization and iterative gradient descent. IEEE Wireless Communication Letter, 11(2), 343–347.

    Article  Google Scholar 

  25. Chen, P., Cao, Z., Chen, Z., & Yu, C. (2019). Sparse off-grid DOA estimation method with unknown mutual coupling effect. Digital Signal Processing, 90, 1–9.

    Article  MathSciNet  Google Scholar 

  26. Chen, P., Cao, Z., Chen, Z., & Wang, X. (2019). Off-grid DOA estimation using sparse bayesian learning in MIMO radar with unknown mutual coupling. IEEE Transactions on Signal Processing, 67(1), 208–220.

    Article  MathSciNet  Google Scholar 

  27. Friedlander, B., & Weiss, A. (1991). Direction finding in the presence of mutual coupling, IEEE Trans. IEEE Transactions on Antennas and Propagation, 39(3), 273–284.

    Article  Google Scholar 

  28. Aich, A., & Palanisamy, P.(2017). “On-grid DOA estimation method using orthogonal matching pursuit,” in 2017 International Conference on Signal Processing and Communication (ICSPC), pp. 483–487.

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 62171089, and in part by the Natural Science Foundation of Sichuan Province under Grant 2022NSFSC0497.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Renting Liu.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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

He, M., Ren, C., Liu, R. et al. Reduced-Dimensional Block Sparse Angle Estimation for Bistatic MIMO Radar with Unknown Mutual Coupling. Wireless Pers Commun 138, 1423–1438 (2024). https://doi.org/10.1007/s11277-024-11462-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-024-11462-z

Keywords

Navigation