Volume 11 Issue 6
Dec.  2022
Turn off MathJax
Article Contents
Abstract
References
Article Navigation >  Journal of Radars  > 2022  >  11(6): 1110-1118
SU Hanning, PAN Jiameng, BAO Qinglong, et al. Anti-interrupted sampling repeater jamming method in the waveform domain before matched filtering[J]. Journal of Radars, 2024, 13(1): 240–252. doi: 10.12000/JR23149
Citation: WANG Bingnan, ZHAO Juanying, LI Wei, et al. Array synthetic aperture ladar with high spatial resolution technology[J]. Journal of Radars, 2022, 11(6): 1110–1118. doi: 10.12000/JR22204
shu

Array Synthetic Aperture Ladar with High Spatial Resolution Technology

DOI: 10.12000/JR22204 CSTR: 32380.14.JR22204
  • 1.

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China

  • 3.

    Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China

  • 4.

    Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200081, China

Funds:  The Major Project of High-Resolution Earth Observation System of China
More Information
  • Corresponding author: ZHAO Juanying, zhaojuanying@163.com
  • Received Date: 2022-10-14
  • Rev Recd Date: 2022-11-25
    • Available Online: 2022-11-28
  • Publish Date: 2022-12-05
    Abstract
  • By extending synthetic aperture technology from the microwave band to the laser wavelength, Synthetic Aperture Ladar (SAL) has long-distance imaging and extremely high spatial resolution independent of the target distance. Presently, the small field of view is the key constraint in SAL ground observation because of the laser diffraction limitation. In this paper, an array SAL technology is proposed. With high-power array transmission, array-balanced detection, and pulse-wise dynamic internal calibration, a multichannel coherent laser transceiver is realized. Meanwhile, the field of view has multiplied. The results of turntable experiments show that the imaging resolution is better than 3 cm (distance) × 1 cm (azimuth). This technology provides a scientific and technical approach to SAL with wider swath imaging in ground observation.

     

    • FullText(HTML)
    • References(14)
  • [1]
    LEWIS T S and HUTCHINS H S. A synthetic aperture at optical frequencies[J]. Proceedings of the IEEE, 1970, 58(4): 587–588. doi: 10.1109/PROC.1970.7698
    [2]
    MARCUS S, COLELLA B D, and GREEN T J. Solid-state laser synthetic aperture radar[J]. Applied Optics, 1994, 33(6): 960–964. doi: 10.1364/AO.33.000960
    [3]
    GREEN T J, MARCUS S, and COLELLA B D. Synthetic-aperture-radar imaging with a solid-state laser[J]. Applied Optics, 1995, 34(30): 6941–6949. doi: 10.1364/AO.34.006941
    [4]
    BASHKANSKY M, LUCKE R L, FUNK E, et al. Two-dimensional synthetic aperture imaging in the optical domain[J]. Optics Letters, 2002, 27(22): 1983–1985. doi: 10.1364/OL.27.001983
    [5]
    BECK S M, BUCK J R, BUELL W F, et al. Synthetic-aperture imaging laser radar: Laboratory demonstration and signal processing[J]. Applied Optics, 2005, 44(35): 7621–7629. doi: 10.1364/AO.44.007621
    [6]
    KRAUSE B W, BUCK J, RYAN C, et al. Synthetic aperture Ladar flight demonstration[C]. Laser Science to Photonic Applications, Baltimore, USA, 2011: 1–2.
    [7]
    郭亮. 合成孔径成像激光雷达实验与算法研究[D]. [博士论文], 西安电子科技大学, 2009: 43–62.

    GUO Liang. Study on experiment and algorithm of synthetic aperture imaging Lidar[D]. [Ph. D. dissertation], Xidian University, 2009: 43–62.
    [8]
    刘立人, 周煜, 职亚楠, 等. 大口径合成孔径激光成像雷达演示样机及其实验室验证[J]. 光学学报, 2011, 31(9): 0900112. doi: 10.3788/AOS201131.0900112

    LIU Liren, ZHOU Yu, ZHI Ya’nan, et al. A large-aperture synthetic aperture imaging Ladar demonstrator and its verification in laboratory space[J]. Acta Optica Sinica, 2011, 31(9): 0900112. doi: 10.3788/AOS201131.0900112
    [9]
    吴谨, 杨兆省, 赵志龙, 等. 单程远场衍射合成孔径激光雷达成像实验室演示[J]. 红外与毫米波学报, 2013, 32(6): 514–518. doi: 10.3724/SP.J.1010.2013.00514

    WU Jin, YANG Zhaosheng, ZHAO Zhilong, et al. Synthetic aperture Ladar imaging with one-way far-field diffraction[J]. Journal of Infrared and Millimeter Waves, 2013, 32(6): 514–518. doi: 10.3724/SP.J.1010.2013.00514
    [10]
    LI Guangzuo, WANG Ning, WANG Ran, et al. Imaging method for airborne SAL data[J]. Electronics Letters, 2017, 53(5): 351–353. doi: 10.1049/el.2016.4205
    [11]
    张珂殊, 潘洁, 王然, 等. 大幅宽激光合成孔径雷达成像技术研究[J]. 雷达学报, 2017, 6(1): 1–10. doi: 10.12000/JR16152

    ZHANG Keshu, PAN Jie, WANG Ran, et al. Study of wide swath synthetic aperture Ladar imaging techology[J]. Journal of Radars, 2017, 6(1): 1–10. doi: 10.12000/JR16152
    [12]
    张波, 周煜, 孙建锋, 等. 多通道宽幅度合成孔径激光成像雷达收发装置优化研究[J]. 光学学报, 2018, 38(5): 0528002. doi: 10.3788/AOS201838.0528002

    ZHANG Bo, ZHOU Yu, SUN Jianfeng, et al. Optimization research on multi-channel wide-swath synthetic aperture imaging Ladar transceiver system[J]. Acta Optica Sinica, 2018, 38(5): 0528002. doi: 10.3788/AOS201838.0528002
    [13]
    李道京, 周凯, 崔岸婧, 等. 多通道逆合成孔径激光雷达成像探测技术和实验研究[J]. 激光与光电子学进展, 2021, 58(18): 1811017. doi: 10.3788/LOP202158.1811017

    LI Daojing, ZHOU Kai, CUI Anjing, et al. Multi-channel inverse synthetic aperture Ladar imaging detection technology and experimental research[J]. Laser &Optoelectronics Progress, 2021, 58(18): 1811017. doi: 10.3788/LOP202158.1811017
    [14]
    META A, HOOGEBOOM P, and LIGTHART L. Range non-linearities correction in FMCW SAR[C]. 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, USA, 2006: 403–406.
    • Relative Articles

  • Relative Articles

    [1]WANG Xiang, WANG Yumiao, CHEN Xingyu, ZANG Chuanfei, CUI Guolong. Deep Learning-based Marine Target Detection Method with Multiple Feature Fusion[J]. Journal of Radars, 2024, 13(3): 554-564. doi: 10.12000/JR23105
    [2]KONG Lingjiang, GUO Shisheng, CHEN Jiahui, WU Peilun, CUI Guolong. Overview and Prospects of Multipath Exploitation Radar Target Detection Technology[J]. Journal of Radars, 2024, 13(1): 23-45. doi: 10.12000/JR23134
    [3]ZHANG Yushi, LI Xiaoyu, ZHANG Jinpeng, XIA Xiaoyun. Sea Clutter Spectral Parameters Prediction and Influence Factor Analysis Based on Deep Learning[J]. Journal of Radars, 2023, 12(1): 110-119. doi: 10.12000/JR22133
    [4]GUAN Jian, LIU Ningbo, WANG Guoqing, DING Hao, DONG Yunlong, HUANG Yong, TIAN Kaixiang, ZHANG Mengyu. Sea-detecting Radar Experiment and Target Feature Data Acquisition for Dual Polarization Multistate Scattering Dataset of Marine Targets（in English）[J]. Journal of Radars, 2023, 12(2): 456-469. doi: 10.12000/JR23029
    [5]DONG Yunlong, ZHANG Zhaoxiang, DING Hao, HUANG Yong, LIU Ningbo. Target Detection in Sea Clutter Using a Three-feature Prediction-based Method[J]. Journal of Radars, 2023, 12(4): 762-775. doi: 10.12000/JR23037
    [6]WU Wenjun, TANG Bo, TANG Jun, HU Yuankui. Waveform Design for Dual-function Radar-communication Systems in Clutter[J]. Journal of Radars, 2022, 11(4): 570-580. doi: 10.12000/JR22105
    [7]ZHANG Chao, WANG Yuanhe, JIANG Xuefeng. Quantum Radar with Vortex Microwave Photons[J]. Journal of Radars, 2021, 10(5): 749-759. doi: 10.12000/JR21095
    [8]LIU Ningbo, DING Hao, HUANG Yong, DONG Yunlong, WANG Guoqing, DONG Kai. Annual Progress of the Sea-detecting X-band Radar and Data Acquisition Program[J]. Journal of Radars, 2021, 10(1): 173-182. doi: 10.12000/JR21011
    [9]WAN Xianrong, LIU Tongtong, YI Jianxin, DAN Yangpeng, HU Xiaokai. System Design and Target Detection Experiments for LTE-based Passive Radar[J]. Journal of Radars, 2020, 9(6): 967-973. doi: 10.12000/JR18111
    [10]CHEN Shichao, GAO Heting, LUO Feng. Target Detection in Sea Clutter Based on Combined Characteristics of Polarization[J]. Journal of Radars, 2020, 9(4): 664-673. doi: 10.12000/JR20072
    [11]GUAN Jian. Summary of Marine Radar Target Characteristics[J]. Journal of Radars, 2020, 9(4): 674-683. doi: 10.12000/JR20114
    [12]XU Shuwen, BAI Xiaohui, GUO Zixun, SHUI Penglang. Status and Prospects of Feature-based Detection Methods for Floating Targets on the Sea Surface (in English)[J]. Journal of Radars, 2020, 9(4): 684-714. doi: 10.12000/JR20084
    [13]LIU Ningbo, DONG Yunlong, WANG Guoqing, DING Hao, HUANG Yong, GUAN Jian, CHEN Xiaolong, HE You. Sea-detecting X-band Radar and Data Acquisition Program (in English)[J]. Journal of Radars, 2019, 8(5): 656-667. doi: 10.12000/JR19089
    [14]Wang Jun, Zheng Tong, Lei Peng, Wei Shaoming. Study on Deep Learning in Radar[J]. Journal of Radars, 2018, 7(4): 395-411. doi: 10.12000/JR18040
    [15]Wang Longgang, Li Lianlin. Short-range Radar Detection with (M, N)-Coprime Array Configurations(in English)[J]. Journal of Radars, 2016, 5(3): 244-253. doi: 10.12000/JR16022
    [16]Ding Hao, Dong Yunlong, Liu Ningbo, Wang Guoqing, Guan Jian. Overview and Prospects of Research on Sea Clutter Property Cognition[J]. Journal of Radars, 2016, 5(5): 499-516. doi: 10.12000/JR16069
    [17]Hu Cheng, Liu Changjiang, Zeng Tao. Bistatic Forward Scattering Radar Detection and Imaging[J]. Journal of Radars, 2016, 5(3): 229-243. doi: 10.12000/JR16058
    [18]Wei Ming-gui, Liang Da-chuan, Gu Jian-qiang, Min Rui, Li Jin, Ouyang Chun-mei, Tian Zhen, He Ming-xia, Han Jia-guang, Zhang Wei-li. Terahertz Radar Imaging Based on Time-domain Spectroscopy[J]. Journal of Radars, 2015, 4(2): 222-229. doi: 10.12000/JR14125
    [19]Chen Xiao-long, Dong Yun-long, Li Xiu-you, Guan Jian. Modeling of Micromotion and Analysis of Properties of Rigid Marine Targets[J]. Journal of Radars, 2015, 4(6): 630-638. doi: 10.12000/JR15079
    [20]Yan Liang, Sun Pei-lin, Yi Lei, Han Ning, Tang Jun. Modeling of Compound Gaussian Sea Clutter Based on Inverse Gaussian Distribution[J]. Journal of Radars, 2013, 2(4): 461-465. doi: 10.3724/SP.J.1300.2013.13083
    • Supplements(0)
    • Cited By

  • Cited by

    Periodical cited type(6)

    1. 邢孟道，马鹏辉，楼屹杉，孙光才，林浩. 合成孔径雷达快速后向投影算法综述. 雷达学报. 2024(01): 1-22 . 本站查看
    2. 周开心，刘丹阳，朱永锋，张永杰，周剑雄. 强杂波背景下调频步进DBS技术研究. 系统工程与电子技术. 2024(09): 2960-2967 .
    3. 匡辉，于海锋，高贺利，刘磊，刘杰，张润宁. 超高分辨率星载SAR系统多子带信号处理技术研究. 信号处理. 2022(04): 879-888 .
    4. 吕明久，陈文峰，徐芳，赵欣，杨军. 基于原子范数最小化的步进频率ISAR一维高分辨距离成像方法. 电子与信息学报. 2021(08): 2267-2275 .
    5. 张亦凡，黄平平，徐伟，谭维贤，高志奇. 星载斜视滑动聚束SAR子孔径成像处理算法研究. 信号处理. 2021(08): 1525-1532 .
    6. 吕明久，徐芳，赵丽，陈莉，陈浩. 载频不同分布方式下RSF波形稀疏重构性能分析. 空军预警学院学报. 2020(05): 319-324 .

    Other cited types(6)

  • Created with Highcharts 5.0.7Amount of accessChart context menuAbstract Views, HTML Views, PDF Downloads StatisticsAbstract ViewsHTML ViewsPDF Downloads2024-052024-062024-072024-082024-092024-102024-112024-122025-012025-022025-032025-04020406080
    Created with Highcharts 5.0.7Chart context menuAccess Class DistributionFULLTEXT: 30.5 %FULLTEXT: 30.5 %META: 62.3 %META: 62.3 %PDF: 7.2 %PDF: 7.2 %FULLTEXTMETAPDF
    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 5.0 %其他: 5.0 %其他: 1.0 %其他: 1.0 %Bacoor: 0.2 %Bacoor: 0.2 %China: 1.8 %China: 1.8 %Gwynn Oak: 0.0 %Gwynn Oak: 0.0 %Kennedy Town: 0.0 %Kennedy Town: 0.0 %Saudi Arabia: 0.1 %Saudi Arabia: 0.1 %Singapore: 0.2 %Singapore: 0.2 %Taichung: 0.0 %Taichung: 0.0 %United States: 0.4 %United States: 0.4 %[]: 0.4 %[]: 0.4 %上海: 1.6 %上海: 1.6 %东京都: 0.0 %东京都: 0.0 %东莞: 0.6 %东莞: 0.6 %中山: 0.1 %中山: 0.1 %临汾: 0.1 %临汾: 0.1 %临沂: 0.2 %临沂: 0.2 %丹东: 0.0 %丹东: 0.0 %丽水: 0.1 %丽水: 0.1 %乌鲁木齐: 0.0 %乌鲁木齐: 0.0 %九江: 0.2 %九江: 0.2 %伦敦: 0.2 %伦敦: 0.2 %佛山: 0.1 %佛山: 0.1 %保定: 0.2 %保定: 0.2 %六安: 0.0 %六安: 0.0 %兰州: 0.1 %兰州: 0.1 %兰辛: 0.1 %兰辛: 0.1 %凤凰城: 0.0 %凤凰城: 0.0 %加利福尼亚: 0.0 %加利福尼亚: 0.0 %北京: 6.5 %北京: 6.5 %十堰: 0.1 %十堰: 0.1 %南京: 2.5 %南京: 2.5 %南充: 0.0 %南充: 0.0 %南宁: 0.1 %南宁: 0.1 %南昌: 0.2 %南昌: 0.2 %南通: 0.1 %南通: 0.1 %卡拉奇: 0.1 %卡拉奇: 0.1 %厦门: 0.0 %厦门: 0.0 %台中: 0.0 %台中: 0.0 %台北: 0.2 %台北: 0.2 %台州: 0.1 %台州: 0.1 %台湾: 0.1 %台湾: 0.1 %台湾省: 0.1 %台湾省: 0.1 %合肥: 0.7 %合肥: 0.7 %周口: 0.0 %周口: 0.0 %呼和浩特: 0.1 %呼和浩特: 0.1 %咸阳: 0.2 %咸阳: 0.2 %哈尔滨: 0.8 %哈尔滨: 0.8 %商洛: 0.1 %商洛: 0.1 %嘉兴: 0.0 %嘉兴: 0.0 %圣彼得堡: 0.2 %圣彼得堡: 0.2 %坦佩: 0.0 %坦佩: 0.0 %大同: 0.0 %大同: 0.0 %大连: 0.1 %大连: 0.1 %天津: 0.7 %天津: 0.7 %太原: 0.2 %太原: 0.2 %威海: 0.1 %威海: 0.1 %孟买: 0.5 %孟买: 0.5 %宁波: 0.0 %宁波: 0.0 %安庆: 0.1 %安庆: 0.1 %安康: 0.1 %安康: 0.1 %宝鸡: 0.1 %宝鸡: 0.1 %宣城: 0.4 %宣城: 0.4 %宿州: 0.0 %宿州: 0.0 %巴中: 0.1 %巴中: 0.1 %常州: 0.1 %常州: 0.1 %广元: 0.0 %广元: 0.0 %广州: 0.9 %广州: 0.9 %库比蒂诺: 0.2 %库比蒂诺: 0.2 %开封: 0.7 %开封: 0.7 %张家口: 1.3 %张家口: 1.3 %张家界: 0.1 %张家界: 0.1 %徐州: 0.2 %徐州: 0.2 %德州: 0.0 %德州: 0.0 %德里: 0.1 %德里: 0.1 %忻州: 0.0 %忻州: 0.0 %恩施: 0.1 %恩施: 0.1 %惠州: 0.0 %惠州: 0.0 %成都: 1.2 %成都: 1.2 %扬州: 0.3 %扬州: 0.3 %新奥尔良: 0.0 %新奥尔良: 0.0 %无锡: 0.1 %无锡: 0.1 %昆明: 0.6 %昆明: 0.6 %晋城: 0.0 %晋城: 0.0 %曼谷: 0.1 %曼谷: 0.1 %朝阳: 0.2 %朝阳: 0.2 %来宾: 0.0 %来宾: 0.0 %杭州: 4.3 %杭州: 4.3 %柳州: 0.1 %柳州: 0.1 %株洲: 0.0 %株洲: 0.0 %格兰特县: 0.0 %格兰特县: 0.0 %桂林: 0.2 %桂林: 0.2 %武汉: 0.9 %武汉: 0.9 %汉中: 0.0 %汉中: 0.0 %江门: 0.0 %江门: 0.0 %沈阳: 0.3 %沈阳: 0.3 %波士顿: 0.0 %波士顿: 0.0 %泰米尔纳德: 0.1 %泰米尔纳德: 0.1 %洛杉矶: 0.1 %洛杉矶: 0.1 %洛阳: 0.1 %洛阳: 0.1 %济南: 0.1 %济南: 0.1 %海口: 0.1 %海口: 0.1 %淮北: 0.0 %淮北: 0.0 %淮南: 0.1 %淮南: 0.1 %深圳: 1.3 %深圳: 1.3 %温州: 0.2 %温州: 0.2 %渭南: 0.2 %渭南: 0.2 %湖州: 0.1 %湖州: 0.1 %湘潭: 0.2 %湘潭: 0.2 %漯河: 0.6 %漯河: 0.6 %潍坊: 0.0 %潍坊: 0.0 %玉林: 0.1 %玉林: 0.1 %盐城: 0.0 %盐城: 0.0 %石家庄: 0.4 %石家庄: 0.4 %福冈县: 0.1 %福冈县: 0.1 %福州: 0.1 %福州: 0.1 %秦皇岛: 0.1 %秦皇岛: 0.1 %米兰: 0.0 %米兰: 0.0 %纽约: 0.0 %纽约: 0.0 %绍兴: 0.0 %绍兴: 0.0 %绵阳: 0.6 %绵阳: 0.6 %芒廷维尤: 25.8 %芒廷维尤: 25.8 %芜湖: 0.1 %芜湖: 0.1 %芝加哥: 0.6 %芝加哥: 0.6 %苏州: 0.5 %苏州: 0.5 %荆州: 0.0 %荆州: 0.0 %菏泽: 0.0 %菏泽: 0.0 %萍乡: 0.1 %萍乡: 0.1 %葫芦岛: 0.0 %葫芦岛: 0.0 %葵涌: 0.2 %葵涌: 0.2 %蚌埠: 0.2 %蚌埠: 0.2 %衡水: 0.1 %衡水: 0.1 %衡阳: 0.0 %衡阳: 0.0 %衢州: 0.1 %衢州: 0.1 %西宁: 19.4 %西宁: 19.4 %西安: 2.7 %西安: 2.7 %西安市鄠邑区: 0.0 %西安市鄠邑区: 0.0 %诺沃克: 0.1 %诺沃克: 0.1 %贵阳: 0.4 %贵阳: 0.4 %运城: 0.4 %运城: 0.4 %邯郸: 0.1 %邯郸: 0.1 %郑州: 0.5 %郑州: 0.5 %重庆: 0.4 %重庆: 0.4 %银川: 0.1 %银川: 0.1 %镇江: 0.1 %镇江: 0.1 %长春: 0.1 %长春: 0.1 %长沙: 1.1 %长沙: 1.1 %长治: 0.1 %长治: 0.1 %雷恩: 0.1 %雷恩: 0.1 %青岛: 0.6 %青岛: 0.6 %香港: 0.1 %香港: 0.1 %香港特别行政区: 0.1 %香港特别行政区: 0.1 %驻马店: 0.0 %驻马店: 0.0 %齐齐哈尔: 0.2 %齐齐哈尔: 0.2 %其他其他BacoorChinaGwynn OakKennedy TownSaudi ArabiaSingaporeTaichungUnited States[]上海东京都东莞中山临汾临沂丹东丽水乌鲁木齐九江伦敦佛山保定六安兰州兰辛凤凰城加利福尼亚北京十堰南京南充南宁南昌南通卡拉奇厦门台中台北台州台湾台湾省合肥周口呼和浩特咸阳哈尔滨商洛嘉兴圣彼得堡坦佩大同大连天津太原威海孟买宁波安庆安康宝鸡宣城宿州巴中常州广元广州库比蒂诺开封张家口张家界徐州德州德里忻州恩施惠州成都扬州新奥尔良无锡昆明晋城曼谷朝阳来宾杭州柳州株洲格兰特县桂林武汉汉中江门沈阳波士顿泰米尔纳德洛杉矶洛阳济南海口淮北淮南深圳温州渭南湖州湘潭漯河潍坊玉林盐城石家庄福冈县福州秦皇岛米兰纽约绍兴绵阳芒廷维尤芜湖芝加哥苏州荆州菏泽萍乡葫芦岛葵涌蚌埠衡水衡阳衢州西宁西安西安市鄠邑区诺沃克贵阳运城邯郸郑州重庆银川镇江长春长沙长治雷恩青岛香港香港特别行政区驻马店齐齐哈尔

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML
    Article views(1409) PDF downloads(233) Cited by(12)
    Proportional views
    Related

    京ICP备20021838号-8   Supported by: Beijing Renhe Information Technology Co. Ltd     百度统计

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return