| 基于压缩感知的步进频雷达目标检测算法 |
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| 引用本文： | 李莹,张弓,陶宇,文方青,贲德.基于压缩感知的步进频雷达目标检测算法[J].现代雷达,2015(9):22-25. |
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| 作者姓名： | 李莹 张弓 陶宇 文方青 贲德 |
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| 作者单位： | 雷达成像与微波光子技术教育部重点实验室;雷达成像与微波光子技术教育部重点实验室;雷达成像与微波光子技术教育部重点实验室;雷达成像与微波光子技术教育部重点实验室;雷达成像与微波光子技术教育部重点实验室;南京电子技术研究所 |
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| 基金项目： | 国家自然科学基金资助项目;南京航空航天大学博士学位论文创新与创优基金资助项目;江苏高校优势学科建设工程资助项目 |
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| 摘 要： | 为了解决压缩感知步进频雷达在低信噪比下的目标检测问题，结合传统雷达的恒虚警检测和压缩感知雷达重构思想，建立基于压缩感知的步进频雷达的目标检测模型，利用复近似消息传递消息的特性，提出了一种基于多脉冲的重构算法，并结合恒虚警检测实现了低信噪比下的压缩感知步进频雷达目标检测。仿真结果表明：文中所提的方法提高了检测概率，改善了目标检测性能。
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| 关 键 词： | 压缩感知 步进频雷达 目标检测 低信噪比 |
Target Detection in Compressive Sensing Based on Step Frequency Radar |
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| LI Ying,ZHANG Gong,TAO Yu,WEN Fangqing and Ben De.Target Detection in Compressive Sensing Based on Step Frequency Radar[J].Modern Radar,2015(9):22-25. |
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| Authors: | LI Ying ZHANG Gong TAO Yu WEN Fangqing and Ben De |
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| Affiliation: | Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics;Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics;Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics;Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics;Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics;Nanjing Research Institute of Electronics Technology |
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| Abstract: | Target detection of step frequency radar (SFR) with compressive sensing (CS) in low signal to noise ratio (SNR) scene is addressed. CS radar is combined with conventional constant false alarm rate (CFAR) processing. The model of target detection in CS based SFR is established. Inspired by CAMP algorithm, we propose a CS reconstruction algorithm with multi pulses. In combination with CFAR detection, radar target detection in CS based SFR is then accomplished in low SNR scene. Simulation results show that the proposed algorithm improves the detection probability and enhances the performance of target detection. |
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| Keywords: | compressive sensing step frequency radar target detection low signal to noise ratio |
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