Volume 11 Issue 3
Jun.  2022
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Article Navigation >  Journal of Radars  > 2022  >  11(3): 376-385
DING Zihang, XIE Junwei, and WANG Bo. Missing covariance matrix recovery with the FDA-MIMO radar using deep learning method[J]. Journal of Radars, 2023, 12(5): 1112–1124. doi: 10.12000/JR23002
Citation: AN Hongyang, SUN Zhichao, WANG Chaodong, et al. Unambiguous imaging method for GEO-LEO bistatic SAR based on joint sequential multiframe and multichannel receiving recovery[J]. Journal of Radars, 2022, 11(3): 376–385. doi: 10.12000/JR21133
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Unambiguous Imaging Method for GEO-LEO Bistatic SAR Based on Joint Sequential Multiframe and Multichannel Receiving Recovery

DOI: 10.12000/JR21133

  • School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Funds:  The National Natural Science Foundation of China (61922023, 61901088, 61771113, 61801099), The China Postdoctoral Science Foundation (2021M690557, 2019M65338), The Postdoctoral Innovation Talent Support Program (BX2021058)
More Information
  • Corresponding author: WU Junjie, junjie_wu@uestc.edu.cn
  • Received Date: 2021-09-18
  • Accepted Date: 2021-11-11
  • Rev Recd Date: 2021-11-10
    • Available Online: 2021-11-15
  • Publish Date: 2021-12-06
    Abstract
  • A geosynchronous (GEO) satellite can provide continuous illumination with broad beam coverage for a Low Earth Orbit (LEO) receiver, used as the transmitting station of bistatic Synthetic Aperture Radar (SAR). Meanwhile, because the bistatic SAR system comprises a separate transmitter and receiver, the LEO receiver can realize multiview imaging such as downward-, forward-, and backward-looking. Therefore, GEO-LEO bistatic SAR is widely used in earth surveying and mapping to reconnaissance and surveillance application. To realize large-scene imaging, the pulse repetition rate of the GEO SAR transmitter should be low. Meanwhile, the LEO SAR receiver introduces a wide Doppler bandwidth, resulting in the azimuth undersampling of the GEO-LEO bistatic SAR. Although the multichannel technology in the receiver can suppress the ambiguity, the multichannel unambiguous recovery method requires numerous channels, resulting in the undersampling of the GEO-LEO bistatic SAR, and hindering the miniaturization of the receiving system. To address the problem of ambiguous imaging of complex observation scenes under the condition of severe azimuth subsampling condition, a sequential joint multiframe and multireceiving channel recovery unambiguous imaging method is proposed. The unambiguous imaging is recovered jointly from the correlation between sequential multiframe observation scenes and multireceiving channel sampling information. First, the unambiguous imaging problem of the GEO-LEO bistatic SAR is modeled as a joint low rank and sparse tensor optimization problem. Second, in the iterative solution of the alternating direction multiplier method, the multireceiving channel information is used to realize the unambiguous imaging of the GEO-LEO bistatic SAR for complex observation scenes. The proposed method can significantly reduce the number of receiving channels required for unambiguous imaging compared with the imaging method based on traditional multichannel The results obtained by the proposed method are validated by simulations and experiments.

     

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    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 6.5 %其他: 6.5 %其他: 1.7 %其他: 1.7 %China: 0.3 %China: 0.3 %Falls Church: 0.0 %Falls Church: 0.0 %Happy Valley: 0.1 %Happy Valley: 0.1 %Kao-sung: 0.1 %Kao-sung: 0.1 %Tottori-shi: 0.2 %Tottori-shi: 0.2 %三亚: 0.0 %三亚: 0.0 %上海: 1.4 %上海: 1.4 %东京: 0.3 %东京: 0.3 %东京都: 0.0 %东京都: 0.0 %东莞: 0.2 %东莞: 0.2 %中卫: 0.2 %中卫: 0.2 %丹东: 0.2 %丹东: 0.2 %乌鲁木齐: 0.0 %乌鲁木齐: 0.0 %九江: 0.0 %九江: 0.0 %九龙城: 0.0 %九龙城: 0.0 %云浮: 0.2 %云浮: 0.2 %京畿道: 0.1 %京畿道: 0.1 %佛山: 0.1 %佛山: 0.1 %六安: 0.0 %六安: 0.0 %兰州: 0.1 %兰州: 0.1 %兰辛: 0.1 %兰辛: 0.1 %内江: 0.1 %内江: 0.1 %北京: 12.2 %北京: 12.2 %十堰: 0.2 %十堰: 0.2 %华沙: 0.3 %华沙: 0.3 %南京: 3.4 %南京: 3.4 %南充: 0.0 %南充: 0.0 %南宁: 0.0 %南宁: 0.0 %南昌: 0.3 %南昌: 0.3 %卡拉奇: 0.0 %卡拉奇: 0.0 %印多尔: 0.1 %印多尔: 0.1 %厦门: 0.0 %厦门: 0.0 %台北: 0.0 %台北: 0.0 %合肥: 0.6 %合肥: 0.6 %吉林: 0.0 %吉林: 0.0 %周口: 0.0 %周口: 0.0 %呼和浩特: 0.1 %呼和浩特: 0.1 %咸阳: 0.0 %咸阳: 0.0 %哈尔滨: 0.2 %哈尔滨: 0.2 %哥伦布: 0.0 %哥伦布: 0.0 %商洛: 0.0 %商洛: 0.0 %喀什: 0.6 %喀什: 0.6 %嘉兴: 0.3 %嘉兴: 0.3 %塔斯卡卢萨: 0.0 %塔斯卡卢萨: 0.0 %大连: 0.1 %大连: 0.1 %天津: 1.2 %天津: 1.2 %太原: 0.0 %太原: 0.0 %威海: 0.0 %威海: 0.0 %娄底: 0.0 %娄底: 0.0 %孟买: 0.1 %孟买: 0.1 %安康: 0.3 %安康: 0.3 %安阳: 0.0 %安阳: 0.0 %宣城: 0.2 %宣城: 0.2 %巴中: 0.0 %巴中: 0.0 %帕萨迪纳: 0.0 %帕萨迪纳: 0.0 %常州: 0.3 %常州: 0.3 %常德: 0.5 %常德: 0.5 %平顶山: 0.0 %平顶山: 0.0 %广州: 1.8 %广州: 1.8 %库比蒂诺: 0.0 %库比蒂诺: 0.0 %延安: 0.2 %延安: 0.2 %开封: 0.6 %开封: 0.6 %弗吉: 0.1 %弗吉: 0.1 %张家口: 3.0 %张家口: 3.0 %张家界: 0.2 %张家界: 0.2 %徐州: 0.2 %徐州: 0.2 %悉尼: 0.1 %悉尼: 0.1 %惠州: 0.1 %惠州: 0.1 %成都: 2.3 %成都: 2.3 %扬州: 0.4 %扬州: 0.4 %新德里: 0.1 %新德里: 0.1 %无锡: 0.2 %无锡: 0.2 %昆明: 1.8 %昆明: 1.8 %晋城: 0.0 %晋城: 0.0 %朝阳: 0.3 %朝阳: 0.3 %来宾: 0.0 %来宾: 0.0 %杭州: 0.9 %杭州: 0.9 %松原: 0.0 %松原: 0.0 %武汉: 1.2 %武汉: 1.2 %汕头: 0.2 %汕头: 0.2 %沈阳: 0.3 %沈阳: 0.3 %河池: 0.0 %河池: 0.0 %泉州: 0.2 %泉州: 0.2 %洛阳: 0.3 %洛阳: 0.3 %济南: 0.0 %济南: 0.0 %海东: 0.1 %海东: 0.1 %海口: 0.0 %海口: 0.0 %淄博: 0.2 %淄博: 0.2 %淮南: 0.0 %淮南: 0.0 %深圳: 1.3 %深圳: 1.3 %温州: 0.3 %温州: 0.3 %湖州: 0.0 %湖州: 0.0 %漯河: 0.9 %漯河: 0.9 %漳州: 0.0 %漳州: 0.0 %潍坊: 0.2 %潍坊: 0.2 %烟台: 0.1 %烟台: 0.1 %焦作: 0.0 %焦作: 0.0 %珠海: 0.0 %珠海: 0.0 %白山: 0.0 %白山: 0.0 %眉山: 0.0 %眉山: 0.0 %石家庄: 0.6 %石家庄: 0.6 %福州: 0.1 %福州: 0.1 %秦皇岛: 0.0 %秦皇岛: 0.0 %纽约: 0.0 %纽约: 0.0 %绍兴: 0.2 %绍兴: 0.2 %绵阳: 0.0 %绵阳: 0.0 %芒廷维尤: 24.1 %芒廷维尤: 24.1 %芝加哥: 0.5 %芝加哥: 0.5 %苏州: 0.1 %苏州: 0.1 %莫斯科: 0.2 %莫斯科: 0.2 %菏泽: 0.2 %菏泽: 0.2 %葫芦岛: 0.0 %葫芦岛: 0.0 %衡水: 0.3 %衡水: 0.3 %衡阳: 1.0 %衡阳: 1.0 %衢州: 1.5 %衢州: 1.5 %襄阳: 0.0 %襄阳: 0.0 %西宁: 8.9 %西宁: 8.9 %西安: 4.2 %西安: 4.2 %诺沃克: 0.3 %诺沃克: 0.3 %贵阳: 0.1 %贵阳: 0.1 %赣州: 0.0 %赣州: 0.0 %达州: 0.1 %达州: 0.1 %迈阿密: 0.0 %迈阿密: 0.0 %运城: 0.4 %运城: 0.4 %邯郸: 0.1 %邯郸: 0.1 %郑州: 0.3 %郑州: 0.3 %鄂州: 0.0 %鄂州: 0.0 %重庆: 0.6 %重庆: 0.6 %钱德勒: 0.0 %钱德勒: 0.0 %铁岭: 0.0 %铁岭: 0.0 %银川: 0.0 %银川: 0.0 %长春: 0.3 %长春: 0.3 %长沙: 2.1 %长沙: 2.1 %阿什本: 0.0 %阿什本: 0.0 %青岛: 0.6 %青岛: 0.6 %首尔: 0.0 %首尔: 0.0 %首尔特别: 0.1 %首尔特别: 0.1 %香港: 0.3 %香港: 0.3 %马鞍山: 0.0 %马鞍山: 0.0 %黄冈: 0.0 %黄冈: 0.0 %齐齐哈尔: 0.6 %齐齐哈尔: 0.6 %其他其他ChinaFalls ChurchHappy ValleyKao-sungTottori-shi三亚上海东京东京都东莞中卫丹东乌鲁木齐九江九龙城云浮京畿道佛山六安兰州兰辛内江北京十堰华沙南京南充南宁南昌卡拉奇印多尔厦门台北合肥吉林周口呼和浩特咸阳哈尔滨哥伦布商洛喀什嘉兴塔斯卡卢萨大连天津太原威海娄底孟买安康安阳宣城巴中帕萨迪纳常州常德平顶山广州库比蒂诺延安开封弗吉张家口张家界徐州悉尼惠州成都扬州新德里无锡昆明晋城朝阳来宾杭州松原武汉汕头沈阳河池泉州洛阳济南海东海口淄博淮南深圳温州湖州漯河漳州潍坊烟台焦作珠海白山眉山石家庄福州秦皇岛纽约绍兴绵阳芒廷维尤芝加哥苏州莫斯科菏泽葫芦岛衡水衡阳衢州襄阳西宁西安诺沃克贵阳赣州达州迈阿密运城邯郸郑州鄂州重庆钱德勒铁岭银川长春长沙阿什本青岛首尔首尔特别香港马鞍山黄冈齐齐哈尔

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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