Azimuth Resolution Enhancement of Real Aperture Radar Using the Accelerated Sparse-TSVD algorithm and Calibrated Radiation Pattern for Discrete and Distributed Targets

Document Type : Original Article

Authors

1 PhD student, Yazd University, Yazd, Iran

2 Assistant Professor, Yazd University, Yazd, Iran

3 Ph.D., Yazd University, Yazd, Iran

4 Master's degree, Yazd University, Yazd, Iran

Abstract

Real aperture radar (RAR) is appealing for land surveying due to its environmental resilience, wide coverage, simplicity, and portability. However, the relatively wide antenna beam results in limited azimuth resolution, constraining image clarity. While super-resolution algorithms can enhance resolution, they face significant challenges when the antenna phase center shifts during scanning. This paper proposes a novel approach that employs a complex antenna pattern based on point target reflections. The proposed method demonstrates an approximate six-fold improvement in azimuth resolution for X-band RAR data, effectively overcoming the limitations of conventional methods in scanning RAR systems.

Keywords


p>Smiley face

[8]  J. Luo et al., "Two-Dimensional Angular Super-Resolution for Airborne Real Aperture Radar by Fast Conjugate Gradient Iterative Adaptive Approach," IEEE Transactions on Aerospace and Electronic Systems, vol. 59, no. 6, pp. 9480-9500, Dec. 2023, doi: 10.1109/TAES.2023.3321261.
[9] Li, Wenchao, et al. "LRSD-ADMM-NET: Simultaneous Super-resolution Imaging and Target Detection for Forward-looking Scanning Radar." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024), doi:10.1109/igarss52108.2023.10283151.
[10]         M. Migliaccio and A. Gambardella, “Microwave radiometer spatial resolution enhancement”, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 5, pp. 1159–1169, May 2005.doi:10.1109/TGRS.2005.844099
[11]         Y. Zha, Y. Zhang, Y. Huang, and J. Yang, “Bayesian angular super-resolution algorithm for real-aperture imaging in forward-looking radar”, Information, vol. 6, no. 4, pp. 650–668, Oct. 2015. doi:10.3390/info6040650
[12]         Y. Zhang, Y. Huang, Y. Zha, and J. Yang, “Super-resolution imaging for forward-looking scanning radar with generalized Gaussian constraint,” Prog. Electromagn. Res., vol. 46, pp. 1–10, Jan. 2016. doi:10.2528/PIERM15120805
[13]         Y. Zhang, A. Jakobsson, D. Mao, Y. Zhang, Y. Huang, and J. Yang, “Generalized time-updating sparse covariance-based spectral estimation,” IEEE Access, vol. 7, pp. 143876-143887, 2019.doi: 10.1109/access.2019.2944788
[14]         Y. Zhang, A. Jakobsson, Y. Zhang, Y. Huang, and J. Yang, “Wideband sparse reconstruction for scanning radar,” IEEE Trans. Geosci. Remote Sens., vol. 56, no. 10, pp. 6055–6068, Oct. 2018. doi: 10.1109/tgrs.2018.2830100
[15]         Y. Zhang, D. Mao, Q. Zhang, Y. Zhang, Y. Huang, and J. Yang, “Airborne forward looking radar super-resolution imaging using iterative adaptive approach,” IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 12, no. 7, pp. 2044–2054, Jul. 2019 .doi: 10.1109/jstars.2019.2920859
[16] https://images.app.goo.gl/byLpec21RS2yPq9m6
[17] https://images.app.goo.gl/XSnbpLCRatxX1A167
[18]         F. Lenti, F. Nunziata, M. Migliaccio, and G. Rodriguez, “Two dimensional TSVD to enhance the spatial resolution of radiometer data,” IEEE Trans. Geosci. Remote Sens., vol. 52, no. 5, pp. 2450–2458, May 2014.doi: 10.1109/tgrs.2013.2261303
[19]         J. D. Shea, B. D. Van Veen, and S. C. Hagness, “A TSVD analysis of microwave inverse scattering for breast imaging,” IEEE Trans. Biomed. Eng., vol. 59, no. 4, pp. 936–945, Apr. 2012. doi: 10.1109/tbme.2011.2176727
[20]         X. Tuo, Y. Zhang, D. Mao, Y. Kang, and Y. Huang, “A radar forward looking super resolution method based on singular value weighted truncation,” in Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), Jul. 2019, pp. 9180–9183. doi: 10.1109/IGARSS.2019.8898704
[21]         P.-A. Barriere, J. Idier, Y. Goussard, and J.-J. Laurin, “Fast solutions of the 2D inverse scattering problem based on a TSVD approximation of the internal field for the forward model,” IEEE Trans. Antennas Propag., vol. 58, no. 12, pp. 4015–4024, Dec. 2010. doi: 10.1109/tap.2010.2078440
[22]         A. Gambardella and M. Migliaccio, “On the super-resolution of microwave scanning radiometer measurements,” IEEE Geosci. Remote Sens. Lett., vol. 5, no. 4, pp. 796–800, Oct. 2008. doi: 10.1109/lgrs.2008.2006285
[23]         M. T. Alonso, P. López-Dekker, and J. J. Mallorquí, “A novel strategy for radar imaging based on compressive sensing,” IEEE Trans. Geosci. Remote Sens., vol. 48, no. 12, pp. 4285–4295, Dec. 2010. doi: 10.1109/tgrs.2010.2051231
[24]         R. Baraniuk and P. Steeghs, “Compressive radar imaging,” IEEE Radar Conf., Apr. 2007, pp. 128–133.
[25]         Q. Zhang, Y. Zhang, Y. Huang, Y. Zhang, W. Li, and J. Yang, “Sparse with fast MM super-resolution algorithm for radar forward-looking imaging,” IEEE Access, vol. 7, pp. 105247–105257, 2019. doi: 10.1109/access.2019.2932612
[26]         Y. Wu, Y. Zhang, D. Mao, Y. Huang, and J. Yang, “Sparse super-resolution method based on truncated singular value decomposition strategy for radar forward-looking imaging,” J. Appl. Remote Sens., vol. 12, no. 3, 2018, Art. no. 03502. doi: 10.1117/1.jrs.12.035021
[27]         Y. Zhang, X. Tuo, Y. Huang, and J. Yang, “A tv forward looking super-resolution imaging method based on TSVD strategy for scanning radar,” IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 7, pp. 4517–4528, 2020. doi: 10.1109/tgrs.2019.2958085
[28]         X. Tuo, Y. Zhang, Y. Zhang, Y. Huang and J. Yang, "Accelerated l1-svd Deconvolution Approach for Real Aperture Radar Super-resolution Imaging," 2022 IEEE Radar Conference (RadarConf22), New York City, NY, USA, 2022, pp. 1-6. doi: 10.1109/RadarConf2248738.2022.9764344
Volume 11, Issue 1
Serial number 29, spring and summer quarterly
August 2023
Pages 43-54
  • Receive Date: 11 June 2023
  • Revise Date: 11 July 2023
  • Accept Date: 30 July 2023
  • Publish Date: 24 August 2023