利用稀疏CP-OFDM的SAR抗干擾成像方法研究
doi: 10.11999/JEIT240092 cstr: 32379.14.JEIT240092
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中國科學(xué)院空天信息創(chuàng)新研究院 北京 100094
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空間信息處理與應(yīng)用系統(tǒng)技術(shù)重點實驗室 北京 100094
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中國科學(xué)院大學(xué)電子電氣與通信工程學(xué)院 北京 101499
Research on SAR Anti-jamming Imaging Method with Sparse CP-OFDM
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Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
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Key Laboratory of Spatial Information Processing and Application System Technology, Beijing 100094, China
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School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101499, China
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摘要: 合成孔徑雷達(dá)(SAR)是一種微波遙感成像雷達(dá)。近年來,隨著數(shù)字化技術(shù)和射頻電子技術(shù)的進步,針對SAR成像的干擾技術(shù)不斷發(fā)展,基于數(shù)字射頻存儲技術(shù)(DRFM)的有源欺騙干擾更是給民用和軍用的SAR成像系統(tǒng)帶來了前所未有的考驗。針對欺騙干擾開展SAR成像抗干擾研究,該文首先引入帶有循環(huán)前綴的正交頻分復(fù)用(CP-OFDM)波形進行正交波形分集設(shè)計與波形優(yōu)化,獲取具備優(yōu)異自相關(guān)峰值旁瓣水平和互相關(guān)峰值水平的CP-OFDM寬帶正交波形集;然后引入稀疏SAR成像理論,將CP-OFDM波形與稀疏SAR成像相結(jié)合,采用稀疏重構(gòu)算法對CP-OFDM回波進行成像,實現(xiàn)具備抗欺騙干擾能力的高質(zhì)量、高精度SAR成像。最終,開展了點目標(biāo)、面目標(biāo)以及基于真實數(shù)據(jù)模擬的復(fù)雜場景仿真實驗,證明了所提方法可以將欺騙干擾產(chǎn)生的假目標(biāo)完全去除,并對旁瓣進行抑制,實現(xiàn)高精度成像。
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關(guān)鍵詞:
- SAR抗干擾 /
- 帶有循環(huán)前綴的正交頻分復(fù)用(CP-OFDM) /
- 波形分集 /
- 稀疏SAR成像
Abstract: Synthetic Aperture Radar (SAR) is a microwave remote sensing imaging radar. In recent years, with the advancement of digital technology and radio frequency electronic technology, the jamming technology of SAR imaging is developed rapidly. The active jamming such as deception jamming based on Digital Radio Frequency Memory (DRFM) technology brings serious challenges to SAR imaging systems for civil use and military use. For research on SAR anti-jamming imaging against deception jamming, firstly, orthogonal waveform diversity design and waveform optimization is carried out for Orthogonal Frequency Division Multiplexing waveforms with Cyclic Prefixes (CP-OFDM). And the CP-OFDM wide band orthogonal waveform set with excellent autocorrelation peak sidelobe level and cross-correlation peak level is obtained. Then the sparse SAR imaging theory is introduced, which is combined with CP-OFDM. By using the sparse reconstruction method, the high-quality and high-precision imaging with anti-jamming capability is realized. Finally, simulation based on point targets, surface targets and real data is conducted, and it is proved that the method can completely remove the false targets generated by deception jamming, suppress sidelobes and achieve high-precision imaging. -
表 1 機載SAR成像參數(shù)
距離向參數(shù) 數(shù)值 單位 方位向參數(shù) 數(shù)值 單位 景中心斜距 30 km 等效雷達(dá)速度 250 m/s 高度 10 km 雷達(dá)工作頻率 9.4 GHz 發(fā)射脈沖時寬 10 μs 合成孔徑長度 850 m LFM信號調(diào)頻率 10 MHz/μs 天線長度 1 m LFM信號帶寬 100 MHz 脈沖重復(fù)時間 1.67 ms CP-OFDM信號帶寬 120 MHz 斜視角 0 ° 距離向采樣率 120 MHz 下載: 導(dǎo)出CSV
表 2 點目標(biāo)和面目標(biāo)成像指標(biāo)
成像方式 點目標(biāo)成像指標(biāo) 面目標(biāo)成像指標(biāo) ISR (dB) SDR (dB) 距離向PSLR(dB) 方位向PSLR(dB) ISR (dB) SDR (dB) LFM匹配濾波 0 5.95 –22.51 –19.84 0 –2.98 CP-OFDM匹配濾波 2.12 3.01 –13.61 –18.34 1.91 –5.85 稀疏CP-OFDM 5.45 $ - \infty $ –319.86 –321.72 3.95 –19.33 下載: 導(dǎo)出CSV
表 3 星載SAR雷達(dá)參數(shù)
距離向參數(shù) 數(shù)值 單位 方位向參數(shù) 數(shù)值 單位 景中心斜距 850 km 等效雷達(dá)速度 7100 m/s 高度 800 km 雷達(dá)工作頻率 5.3 GHz 發(fā)射脈沖時寬 40 μs 合成孔徑長度 4800 m LFM信號調(diào)頻率 0.5 MHz/μs 天線長度 10 m LFM信號帶寬 20 MHz 脈沖重復(fù)時間 588.24 μs CP-OFDM信號帶寬 24 MHz 斜視角 0 ° 距離向采樣率 24 MHz 下載: 導(dǎo)出CSV
表 4 復(fù)雜場景干擾抑制比和信號失真比(dB)
成像方式 ISR SDR LFM匹配濾波 0 –11.96 CP-OFDM匹配濾波 0.15 –14.55 稀疏CP-OFDM 0.27 –19.50 下載: 導(dǎo)出CSV
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[1] 黃巖, 趙博, 陶明亮, 等. 合成孔徑雷達(dá)抗干擾技術(shù)綜述[J]. 雷達(dá)學(xué)報, 2020, 9(1): 86–106. doi: 10.12000/JR19113.HUANG Yan, ZHAO Bo, TAO Mingliang, et al. Review of synthetic aperture radar interference suppression[J]. Journal of Radars, 2020, 9(1): 86–106. doi: 10.12000/JR19113. [2] FENG Qingqing, XU Huaping, WU Zhefeng, et al. Deceptive jamming suppression for SAR based on time-varying initial phase[C]. 2016 IEEE International Geoscience and Remote Sensing Symposium, Beijing, China, 2016: 4996–4999. doi: 10.1109/IGARSS.2016.7730303. [3] 崔國龍, 樊濤, 孔昱凱, 等. 機載雷達(dá)脈間波形參數(shù)偽隨機跳變技術(shù)[J]. 雷達(dá)學(xué)報, 2022, 11(2): 213–226. doi: 10.12000/JR21189.CUI Guolong, FAN Tao, KONG Yukai, et al. Pseudo-random agility technology for interpulse waveform parameters in airborne radar[J]. Journal of Radars, 2022, 11(2): 213–226. doi: 10.12000/JR21189. [4] QIU Xiaoyan, ZHANG Tianjian, LI Shuangshuang, et al. SAR anti-jamming technique using orthogonal LFM-PC hybrid modulated signal[C]. 2018 China International SAR Symposium, Shanghai, China, 2018: 1–6. doi: 10.1109/SARS.2018.8551996. [5] QIU Xiaoyan, WANG Pengfei, JIANG Jie, et al. Research on SAR anti-jamming technique based on orthogonal LFM-PC signals with adaptive initial phase[C]. 2021 2nd China International SAR Symposium (CISS), Shanghai, China, 2021: 1–5. doi: 10.23919/CISS51089.2021.9652198. [6] ZHOU Kai, LI Dexin, SONG Xiaoji, et al. A method of improving the correlation properties of OFDM chirp waveform diversity[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 18(9): 1550–1554. doi: 10.1109/LGRS.2020.3003739. [7] ZHANG Tianxian and XIA Xianggen. OFDM synthetic aperture radar imaging with sufficient cyclic prefix[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(1): 394–404. doi: 10.1109/TGRS.2014.2322813. [8] ZHANG Tianxian, XIA Xianggen, and KONG Lingjiang. IRCI free range reconstruction for SAR imaging with arbitrary length OFDM pulse[J]. IEEE Transactions on Signal Processing, 2014, 62(18): 4748–4759. doi: 10.1109/TSP.2014.2339796. [9] 趙金珊, 全英匯, 劉代軍, 等. 基于遺傳算法的OFDM雷達(dá)低旁瓣波形優(yōu)化設(shè)計[J]. 航空兵器, 2021, 28(5): 76–80. doi: 10.12132/ISS N.1673-5048.2020.0258. doi: 10.12132/ISSN.1673-5048.2020.0258.ZHAO Jinshan, QUAN Yinghui, LIU Daijun, et al. Optimal design of OFDM radar low sidelobe waveform based on genetic algorithm[J]. Aero Weaponry, 2021, 28(5): 76–80. doi: 10.12132/ISS N.1673-5048.2020.0258. doi: 10.12132/ISSN.1673-5048.2020.0258. [10] GARMATYUK D and BRENNEMAN M. Adaptive multicarrier OFDM SAR signal processing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3780–3790. doi: 10.1109/TGRS.2011.2165546. [11] YU Xiang, FU Yaowen, NIE Lei, et al. IRCI-free CP-OFDM SAR signal processing[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(1): 50–54. doi: 10.1109/LGRS.2018.2867484. [12] ZHANG Bingchen, HONG Wen, and WU Yirong. Sparse microwave imaging: Principles and applications[J]. Science China Information Sciences, 2012, 55(8): 1722–1754. doi: 10.1007/s11432-012-4633-4. [13] XU Gang, ZHANG Bangjie, YU Hanwen, et al. Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends[J]. IEEE Geoscience and Remote Sensing Magazine, 2022, 10(4): 32–69. doi: 10.1109/MGR S.2022.3218801. doi: 10.1109/MGRS.2022.3218801. [14] GU Fufei, ZHANG Qun, LOU Hao, et al. Two-dimensional sparse synthetic aperture radar imaging method with stepped-frequency waveform[J]. Journal of Applied Remote Sensing, 2015, 9(1): 096099. doi: 10.1117/1.JRS.9.096099. [15] ZHOU Kai, LI Dexin, HE Feng, et al. A sparse imaging method for frequency agile SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5223616. doi: 10.1109/TGRS.2022.3151079. [16] ZHOU Feng, TAO Mingling, BAI Xueru, et al. Narrow-band interference suppression for SAR based on independent component analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(10): 4952–4960. doi: 10.1109/TGRS.2013.2244605. -