volume | PIER Journals

Abstract

Available of multiple illuminators in a multistatic airborne passive synthetic aperture radar (SAR) system can enhance SAR imaging quality. In this paper, a new imaging algorithm based on two-level block sparsity for a multistatic airborne passive SAR system is proposed. The proposed imaging algorithm named by two-level block matching pursuit (BMP) algorithm utilizes both the spatially clustered property of observed targets and joint sparsity of the multistatic observation, i.e. two-level block sparsity to achieve imaging reconstruction of an observed scene. The simulation results show that the proposed two-level BMP imaging algorithm for the multistatic airborne passive SAR system can reduce imaging reconstruction time and provide enhanced imaging reconstruction quality compared to the state-of-the-art structured sparse imaging algorithm.

1. Yonel, B., E. Mason, and B. Yazıcı, "Deep learning for passive synthetic aperture radar," IEEE J. Sel. Topics Signal Process., Vol. 12, No. 1, 90-103, Feb. 2018.
doi:10.1109/JSTSP.2017.2784181 Google Scholar

2. Wan, X., J. Yi, Z. Zhao, and H. Ke, "Experimental research for CMMB-based passive radar under a multipath environment," IEEE Trans. Aerosp. Electron. Syst., Vol. 50, No. 1, 70-85, Jan. 2014.
doi:10.1109/TAES.2013.120737 Google Scholar

3. Liu, F., M. Antoniou, Z. Zeng, and M. Cherniakov, "Coherent change detection using passive GNSS-based BSAR: experimental proof of concept," IEEE Trans. Geosci. Remote Sens., Vol. 51, No. 8, 4544-4555, Aug. 2013.
doi:10.1109/TGRS.2012.2231082 Google Scholar

4. Pastina, D., et al. "Maritime moving target long time integration for GNSS-based passive bistatic radar," IEEE Trans. Aerosp. Electron. Syst., Vol. 54, No. 6, 3060-3083, Dec. 2018.
doi:10.1109/TAES.2018.2840298 Google Scholar

5. Tan, D. K. P., M. Lesturgie, H. Sun, and Y. Lu, "Space-time interference analysis and suppression for airborne passive radar using transmissions of opportunity," IET Radar, Sonar and Navigation, Vol. 8, No. 2, 142-152, Feb. 2014.
doi:10.1049/iet-rsn.2013.0190 Google Scholar

6. Deng, Y., J. Wang, Z. Luo, and S. Guo, "Cascaded suppression method for airborne passive radar with contaminated reference signal," IEEE Access, Vol. 7, 50317-50329, 2019.
doi:10.1109/ACCESS.2019.2911136 Google Scholar

7. Yang, P., X. L. Yu, Z. Chai, D. Zhang, Q. Yue, and J. Yang, "Clutter cancellation along the clutter ridge for airborne passive radar," IEEE Geosci. Remote Sens. Lett., Vol. 14, No. 6, 951-955, Jun. 2017.
doi:10.1109/LGRS.2017.2689076 Google Scholar

8. Berthillot, C., A. Santori, O. Rabaste, D. Poullin, and M. Lesturgie, "BEM reference signal estimation for an airborne passive radar antenna array," IEEE Trans. Aerosp. Electron. Syst., Vol. 53, No. 6, 2833-2845, Dec. 2017.
doi:10.1109/TAES.2017.2716458 Google Scholar

9. Wang, L., C. E. Yarman, and B. Yazici, "Doppler-Hitchhiker: A novel passive synthetic aperture radar using ultranarrowband sources of opportunity," IEEE Trans. Geosci. Remote Sens., Vol. 49, No. 10, 3521-3537, Oct. 2011.
doi:10.1109/TGRS.2011.2142420 Google Scholar

10. Dawidowicz, B., K. S. Kulpa, M. Malanowski, J. Misiurewicz, P. Samczynski, and M. Smolarczyk, "DPCA detection of moving targets in airborne passive radar," IEEE Trans. Aerosp. Electron. Syst., Vol. 48, No. 2, 1347-1357, Apr. 2012.
doi:10.1109/TAES.2012.6178066 Google Scholar

11. Gromek, D., K. Kulpa, and P. Samczynski, "Experimental results of passive SAR imaging using DVB-T illuminators of opportunity," IEEE Geosci. Remote Sens. Lett., Vol. 13, No. 8, 1124-1128, Aug. 2016.
doi:10.1109/LGRS.2016.2571901 Google Scholar

12. Gromek, D., K. Radecki, J. Drozdowicz, P. Samczynski, and J. Szabatin, "Passive SAR imaging using DVB-T illumination for airborne applications," IET Radar, Sonar and Navigation, Vol. 13, No. 2, 213-221, Feb. 2019.
doi:10.1049/iet-rsn.2018.5123 Google Scholar

13. Liu, C. C. and W. D. Chen, "Sparse self-calibration imaging via iterative MAP in FM-based distributed passive radar," IEEE Geosci. Remote Sens. Lett., Vol. 10, No. 3, 538-542, Oct. 2013.
doi:10.1109/LGRS.2012.2212272 Google Scholar

14. Qiu, W., et al. "Compressive sensing-based algorithm for passive bistatic ISAR with DVB-T signals," IEEE Trans. Aerosp. Electron. Syst., Vol. 51, No. 3, 2166-2180, Jul. 2015.
doi:10.1109/TAES.2015.130761 Google Scholar

15. Yu, X. F., T. Y. Wang, X. F. Lu, C. Chen, and W. D. Chen, "Sparse passive radar imaging based on DVB-S using the Laplace-SLIM algorithm," 2014 International Radar Conference, 1-4, Lille, 2014. Google Scholar

16. Zhang, Y. D., M. G. Amin, and B. Himed, "Structure-aware sparse reconstruction and applications to passive multistatic radar," IEEE Aerosp. Electron. Syst. Mag., Vol. 32, No. 2, 68-78, Feb. 2017.
doi:10.1109/MAES.2017.160021 Google Scholar

17. Wu, Q., Y. D. Zhang, M. G. Amin, and B. Himed, "High-resolution passive SAR imaging exploiting structured Bayesian compressive sensing," IEEE J. Sel. Topics Signal Process., Vol. 9, No. 8, 1484-1497, Dec. 2015.
doi:10.1109/JSTSP.2015.2479190 Google Scholar

18. Wang, X., G. Li, Y. Liu, and M. G. Amin, "Two-level block matching pursuit for polarimetric through-wall radar imaging," IEEE Trans. Geosci. Remote Sens., Vol. 56, No. 3, 1533-1545, Mar. 2018.
doi:10.1109/TGRS.2017.2764920 Google Scholar

19. Cevher, V., P. Indyk, L. Carin, and R. G. Baraniuk, "Sparse signal recovery and acquisition with graphical models," IEEE Signal Process. Mag., Vol. 27, No. 6, 92-103, Nov. 2010. Google Scholar

20. Cevher, V., M. F. Duarte, C. Hegde, and R. G. Baraniuk, "Sparse signal recovery using Markov random fields," Proc. Adv. Neural. Inf., 257-264, 2009. Google Scholar

21. Tropp, J. A., A. C. Gilbert, and M. J. Strauss, "Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit?," Signal Process., Vol. 86, No. 3, 572-588, Mar. 2006.
doi:10.1016/j.sigpro.2005.05.030 Google Scholar

22. Koller, D. and N. Friedman, Probabilistic Graphical Models-Principles and Techniques, MIT Press, Cambridge, MA, USA, 2009.

23. Ward, R., "Compressed sensing with cross validation," IEEE Trans. on Inf. Theory, Vol. 55, No. 12, 5773-5782, Dec. 2009.
doi:10.1109/TIT.2009.2032712 Google Scholar

24. Zhang, J., L. Chen, P. T. Boufounos, and Y. Gu, "On the theoretical analysis of cross validation in compressive sensing," Proceeding of the 2014 IEEE International Conference on Acoustic, Speech, and Signal Processing, ICASSP 2014, 3370-3374, Italy, 2014. Google Scholar

25. Seng, C. H., A. Bouzerdoum, M. G. Amin, and S. L. Phung, "Probabilistic fuzzy image fusion approach for radar through wall sensing," IEEE Trans. Image Process., Vol. 22, No. 12, 4938-4951, Dec. 2013.
doi:10.1109/TIP.2013.2279953 Google Scholar

Dr. Lele Qu

Dr. Yu Liu