Optimal Sub-band Selection Algorithm for Pseudo-color Image Synthesis in Microwave Photonic SAR

HAI Yu; LIU Ling; LI Zhongyu; PU Wei; WANG Xiaoting; WU Junjie; LI Wangzhe; LI Ruoming; HUANG Yulin; YANG Jianyu

doi:10.12000/JR23204

Volume 13 Issue 2

Apr. 2024

Turn off MathJax

Article Contents

Abstract

References

Article Navigation > Journal of Radars > 2024 > 13(2): 485-499

HUA Wenqiang, WANG Shuang, GUO Yanhe, et al. Semi-supervised PolSAR image classification based on the neighborhood minimum spanning tree[J]. Journal of Radars, 2019, 8(4): 458–470. doi: 10.12000/JR18104

Citation:

HAI Yu, LIU Ling, LI Zhongyu, et al. Optimal sub-band selection algorithm for pseudo-color image synthesis in microwave photonic SAR[J]. Journal of Radars, 2024, 13(2): 485–499. doi: 10.12000/JR23204

Citation:

PDF( 13690 KB)

Optimal Sub-band Selection Algorithm for Pseudo-color Image Synthesis in Microwave Photonic SAR

DOI: 10.12000/JR23204

1.
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
3.
The National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China

Funds: The National Natural Science Foundation of China (62171084, 61922023, 62101096), Science and Technology on Electronic Information Control Laboratory Foundation

More Information

Corresponding author: LI Zhongyu, zhongyu_li@uestc.edu.cn; WU Junjie, junjie_wu@uestc.edu.cn
Received Date: 2023-10-20
Rev Recd Date: 2023-12-15

Available Online: 2023-12-19

Publish Date: 2024-01-16

Abstract

Abstract

Microwave Photonic (MWP) radars have remarkably improved traditional microwave radar hardware architectures using photonics devices. With the exceptional physical properties of photonic devices, MWP radars can emit ultra-wideband, high-linearity, high-quality linear frequency modulation signals, allowing ultra-high-resolution target imaging and detection. Different target regions exhibit distinct responses to different frequency signals during target imaging and detection due to their diverse structures and characteristics. Therefore, MWP radars have the potential to generate pseudo-color images based on scattering differences, further enhancing the information retrieval capability of MWP Synthetic Aperture Radar (MWP-SAR). Pseudo-color images generated using traditional remote sensing techniques cannot achieve centimeter-level resolution. Therefore, we propose a method for generating pseudo-color images while maintaining the resolution of MWP-SAR. The algorithm first determines an optimal sub-band echo search model and subsequently employs the optimal sub-band search algorithm to process the ultra-wideband echoes to obtain sub-band echo channels with the largest scattering characteristic differences. The multi-sub-band images are then color-composited to generate pseudo-color images that best describe the target scattering characteristics. However, to ensure the high resolution of MWP-SAR, a fusion model is established to combine the full-resolution SAR image with the multi-sub-band image. Finally, full-resolution pseudo-color images are successfully synthesized using the measured airborne MWP-SAR data, validating the effectiveness of the algorithm. This algorithm enables MWP-SAR to obtain more target information during imaging, offering assistance in implementing imaging radar and microwave vision.
- Microwave Photonics (MWP),
- Synthetic Aperture Radar (SAR),
- Pseudo-color image,
- Scattering characteristics,
- Optimal sub-band

FullText(HTML)

References(28)

References

[1]	SEEDS A J and WILLIAMS K J. Microwave photonics[J]. Journal of Lightwave Technology, 2006, 24(12): 4628–4641. doi: 10.1109/JLT.2006.885787.
[2]	KIPPENBERG T J, HOLZWARTH R, and DIDDAMS S A. Microresonator-based optical frequency combs[J]. Science, 2011, 332(6029): 555–559. doi: 10.1126/science.1193968.
[3]	PAN Shilong and ZHANG Yamei. Microwave photonic radars[J]. Journal of Lightwave Technology, 2020, 38(19): 5450–5484. doi: 10.1109/JLT.2020.2993166.
[4]	ZHANG Fangzheng, GUO Qingshui, WANG Ziqian, et al. Photonics-based broadband radar for high-resolution and real-time inverse synthetic aperture imaging[J]. Optics Express, 2017, 25(14): 16274–16281. doi: 10.1364/oe.25.016274.
[5]	MELO S, PINNA S, BOGONI A, et al. Dual-use system combining simultaneous active radar & communication, based on a single photonics-assisted transceiver[C]. 2016 17th International Radar Symposium, Krakow, Poland, 2016: 1–4. doi: 10.1109/IRS.2016.7497379.
[6]	RASHIDINEJAD A and WEINER A M. Photonic radio-frequency Arbitrary waveform generation with maximal time-bandwidth product capability[J]. Journal of Lightwave Technology, 2014, 32(20): 3383–3393. doi: 10.1109/JLT.2014.2331491.
[7]	SIMPSON T B, LIU J M, HUANG K F, et al. Nonlinear dynamics induced by external optical injection in semiconductor lasers[J]. Quantum and Semiclassical Optics: Journal of the European Optical Society Part B, 1997, 9(5): 765–784. doi: 10.1088/1355-5111/9/5/009.
[8]	SERAFINO G, NOVIELLO C, MARESCA S, et al. Experimental dual-band coherent photonics-based radar network with ISAR imaging[C]. 2022 IEEE Radar Conference, New York City, USA, 2022: 1–6. doi: 10.1109/RadarConf2248738.2022.9763913.
[9]	JIANG Wen, LIU Jianwei, YANG Jiyao, et al. A novel multiband fusion method based on a modified RELAX algorithm for high-resolution and anti-non-Gaussian colored clutter microwave imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 60: 5105312. doi: 10.1109/TGRS.2021.3109724.
[10]	DEVGAN P S, URICK V J, DIEHL J F, et al. Improvement in the phase noise of a 10 GHz optoelectronic oscillator using all-photonic gain[J]. Journal of Lightwave Technology, 2009, 27(15): 3189–3193. doi: 10.1109/JLT.2008.2009472.
[11]	YAO Jianping. Microwave photonics[J]. Journal of Lightwave Technology, 2009, 27(3): 314–335. doi: 10.1109/JLT.2008.2009551.
[12]	LI Ruoming, LI Wangzhe, DONG Yongwei, et al. An ultrahigh-resolution continuous wave synthetic aperture radar with photonic-assisted signal generation and dechirp processing[C]. 2020 17th European Radar Conference, Utrecht, Netherlands, 2021: 13–16. doi: 10.1109/EuRAD48048.2021.00015.
[13]	WANG Anle, WO Jianghai, LUO Xiong, et al. Ka-band microwave photonic ultra-wideband imaging radar for capturing quantitative target information[J]. Optics Express, 2018, 26(16): 20708–20717. doi: 10.1364/OE.26.020708.
[14]	SERAFINO G, MARESCA S, DI MAURO L, et al. A photonics-assisted multi-band MIMO radar network for the port of the future[J]. IEEE Journal of Selected Topics in Quantum Electronics, 2021, 27(6): 6000413. doi: 10.1109/JSTQE.2021.3092880.
[15]	MARESCA S, SERAFINO G, NOVIELLO C, et al. Field trial of a coherent, widely distributed, dual-band photonics-based MIMO radar with ISAR imaging capabilities[J]. Journal of Lightwave Technology, 2022, 40(20): 6626–6635. doi: 10.1109/JLT.2022.3182421.
[16]	PAN Shilong and ZHU Dan. Broadband cognitive radio enabled by photonics[C]. 45th European Conference on Optical Communication, Dublin, Ireland, 2019: 1–3. doi: 10.1049/cp.2019.0776.
[17]	PAN Shilong, YE Xingwei, ZHANG Yamei, et al. Microwave photonic array radars[J]. IEEE Journal of Microwaves, 2021, 1(1): 176–190. doi: 10.1109/JMW.2020.3034583.
[18]	潘时龙, 朱丹. 微波光子认知雷达技术[J]. 雷达科学与技术, 2021, 19(2): 117–129. doi: 10.3969/j.issn.1672-2337.2021.02.001. PAN Shilong and ZHU Dan. A microwave photonic cognitive radar[J]. Radar Science and Technology, 2021, 19(2): 117–129. doi: 10.3969/j.issn.1672-2337.2021.02.001.
[19]	CHANDRAKANTH R, SAIBABA J, VARADAN G, et al. Feasibility of high resolution SAR and multispectral data fusion[C]. 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, Canada, 2011: 356–359. doi: 10.1109/IGARSS.2011.6048972.
[20]	YOKOYA N, GROHNFELDT C, and CHANUSSOT J. Hyperspectral and multispectral data fusion: A comparative review of the recent literature[J]. IEEE Geoscience and Remote Sensing Magazine, 2017, 5(2): 29–56. doi: 10.1109/MGRS.2016.2637824.
[21]	邓旭, 徐新, 董浩. 单极化合成孔径雷达图像颜色特征编码与分类[J]. 计算机应用, 2018, 38(7): 2056–2063. doi: 10.11772/j.issn.1001-9081.2017112780. DENG Xu, XU Xin, and DONG Hao. Color feature coding and classification of single polarized synthetic aperture radar image[J]. Journal of Computer Applications, 2018, 38(7): 2056–2063. doi: 10.11772/j.issn.1001-9081.2017112780.
[22]	ZHANG Xinzheng, XIA Jili, TAN Xiaoheng, et al. PolSAR image classification via learned superpixels and QCNN integrating color features[J]. Remote Sensing, 2019, 11(15): 1831. doi: 10.3390/rs11151831.
[23]	FRANCESCHETTI G, LANARI R, PASCAZIO V, et al. WASAR: A wide-angle SAR processor[J]. IEE Proceedings F (Radar and Signal Processing), 1992, 139(2): 107–114. doi: 10.1049/ip-f-2.1992.0014.
[24]	INOUE Y, KUROSU T, MAENO H, et al. Season-long daily measurements of multifrequency (Ka, Ku, X, C, and L) and full-polarization backscatter signatures over paddy rice field and their relationship with biological variables[J]. Remote Sensing of Environment, 2002, 81(2/3): 194–204. doi: 10.1016/S0034-4257(01)00343-1.
[25]	RANSON K J and SUN Guoqing. Mapping biomass of a northern forest using multifrequency SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(2): 388–396. doi: 10.1109/36.295053.
[26]	HAI Yu, LI zhongyu, WU Junjie, et al. Microwave photonic SAR high-precision imaging based on optimal subaperture division[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5232317. doi: 10.1109/TGRS.2022.3192583.
[27]	徐丰, 金亚秋. 从物理智能到微波视觉[J]. 科技导报, 2018, 36(10): 30–44. doi: 10.3981/j.issn.1000-7857.2018.10.004. XU Feng and JIN Yaqiu. From the emergence of intelligent science to the research of microwave vision[J]. Science & Technology Review, 2018, 36(10): 30–44. doi: 10.3981/j.issn.1000-7857.2018.10.004.
[28]	LI Ruoming, LI Wangzhe, DONG Yongwei, et al. FDIR—a wideband photonic-assisted SAR system[J]. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59(4): 4333–4346. doi: 10.1109/TAES.2023.3240111.