[1] 陈小龙, 关键, 黄勇, 等. 雷达低可观测目标探测技术[J]. 科技导报, 2017, 35(11):30-38. Chen Xiaolong, Guan Jian, Huang Yong, et al. Radar low-observable target detection[J]. Science & Technology Review, 2017, 35(11):30-38.
[2] 何友, 黄勇, 关键, 等. 海杂波中的雷达目标检测技术综述[J]. 现代雷达, 2014, 36(12):1-9. He You, Huang Yong, Guan Jian, et al. An overview on radar target de-tection in sea clutter[J]. Modern Radar, 2014, 36(12):1-9.
[3] 陈小龙, 关键, 何友. 微多普勒理论在海面目标检测中的应用及展望[J]. 雷达学报, 2013, 2(1):123-134. Chen Xiaolong, Guan jian, He You. Applications and prospect of micromotion theory in the detection of sea surface target[J]. Journal of Ra-dars, 2013, 2(1):123-134.
[4] 陈小龙, 关键, 何友, 等. 高分辨稀疏表示及其在雷达动目标检测中的应用[J]. 雷达学报, 2017, 6(3):239-251. Chen Xiaolong, Guan Jian, He You, et al. High-resolution sparse repre-sentation and its applications in radar moving target detection[J]. Jour-nal of Radars, 2017, 6(3):239-251.
[5] 许稼, 彭应宁, 夏香根, 等. 空时频检测前聚焦雷达信号处理方法[J]. 雷达学报, 2014, 3(2):129-141. Xu Jia, Peng Yingning, Xia Xianggen, et al. Radar signal processing method of space-time-frequency focus-before-detects[J]. Journal of Ra-dars, 2014, 3(2):129-141.
[6] 陈唯实, 李敬. 雷达探鸟技术发展与应用综述[J]. 现代雷达, 2017, 39(2):7-17. Chen Weishi, Li Jing. Review on development and applications of avian radar technology[J]. Modern Radar, 2017, 39(2):7-17.
[7] 罗宏伟. 试论大型活动安保工作中"低慢小" 目标的防范与处置[J]. 武警学院学报, 2015, 31(9):27-30. Luo Hongwei. Strengthening LSS target defense for large activities[J]. Journal Of Chinese People's Armed Police Force Academy, 2015, 31(9):27-30.
[8] Chen X L, Guan J, Bao Z, et al. Detection and extraction of target with micromotion in spiky sea clutter via short-time fractional fourier trans-form[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013, 52(2):1002-1018.
[9] Chen X L, Guan J, Liu N B, et al. Detection of a low observable seasurface target with micromotion via the radon-linear canonical transform[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(7):1225-1229.
[10] 徐文, 鄢社锋, 季飞, 等. 海洋信息获取、传输、处理及融合前沿研究评述[J]. 中国科学(信息科学), 2016, 46(8):1053-1085. Xu Wen, Yan Shefeng, Ji Fei, et al. Marine information gathering, transmission, processing, and fusion:Current status and future trends[J]. Scientia Sinica Informationis, 2016, 46(8):1053-1085.
[11] 陈小龙, 关键, 董云龙, 等. 稀疏域海杂波抑制与微动目标检测方法[J]. 电子学报, 2016, 44(4):860-867. Chen Xiaolong, Guan Jian, Dong Yunlong, et al. Sea clutter suppres-sion and micromotion target detection in sparse domain[J]. Chinese Journal of Electronics, 2016, 44(4):860-867.
[12] Lei Z, Ming L, Xiaowei Z, et al. An efficient method for detecting slow-moving weak targets in sea clutter based on time-frequency iter-ation decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(6):3659-3672.
[13] Chen V C, Fayin L, Ho S S, et al. Micro-Doppler effect in radar:Phe-nomenon, model, and simulation study[J]. IEEE Transactions on Aero-space and Electronic Systems, 2006, 42(1):2-21.
[14] 庄钊文, 刘永祥, 黎湘. 目标微动特性研究进展[J]. 电子学报, 2007, 35(3):520-525. Zhuang Zhaowen, Liu Yongxiang, Li Xiang. The achievements of tar-get characteristic with micro-motion[J]. Chinese Journal of Electron-ics, 2007, 35(3):520-525.
[15] Luo Y, Zhang Q, Yuan N, et al. Three-dimensional precession feature extraction of space targets in distributed radar networks[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2):1313-1329.
[16] 李开明, 李长栋, 李松, 等. 基于Gabor变换的微动目标微多普勒分析与仿真[J]. 空军工程大学学报(自然科学版), 2010, 11(1):40-94. Li Kaiming, Li Changdong, Li Song, et al. Analysis and simulation for micro-Doppler information of micro-motion target based on Gabor transformation[J]. Journal of Air Force Engineering University (Natural Science Edition), 2010, 11(1):40-94.
[17] Wu X, Liu T. Spectral decomposition of seismic data with reassigned smoothed pseudo Wigner-Ville distribution[J]. Journal of Applied Geo-physics, 2009, 68(3):386-393.
[18] Chandra Sekhar S, Sreenivas T V. Effect of interpolation on PWVD computation and instantaneous frequency estimation[J]. Signal process-ing, 2004, 84(1):107-116.
[19] Wang Y, Jiang Y C. New time-frequency distribution based on the polynomial Wigner-Ville distribution and L class of Wigner-Ville dis-tribution[J]. IET Signal Processing, 2010, 4(2):130-136.
[20] 许世军, 罗迎, 陈天平. 低信噪比条件下雷达目标微多普勒信息提取[J]. 弹箭与制导学报, 2010, 30(3):148-150. Xu Shijun, Luo Ying, Chen Tianping. Extraction of micro-doppler in-formation with low signal-to-noise ratio[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2010, 30(3):148-150.
[21] Almeida L B. The fractional Fourier transform and time-frequency rep-resentations[J]. IEEE Transactions on Signal Processing, 1994, 42(11):3084-3091.
[22] 陶然, 邓兵, 王越. 分数阶傅里叶变换及其应用[M]. 北京:清华大学出版社, 2009. Tao Ran, Deng Bing, Wang Yue. The fractional Fourier transform and its application[M]. Beijing:Tsinghua University Press, 2009.
[23] Guan J, Chen X L, Huang Y, et al. Adaptive fractional Fourier trans-form-based detection algorithm for moving target in heavy sea clutter[J]. IET Radar, Sonar and Navigation, 2012, 6(5):389-401.
[24] 陈小龙, 关键, 黄勇, 等. 分数阶傅里叶变换在动目标检测和识别中的应用:回顾和展望[J]. 信号处理, 2013, 29(1):85-97. Chen Xiaolong, Guan Jian, Huang Yong, et al. Application of fraction-al Fourier transform in moving target detection and recognition:Devel-opment and prospect[J]. Journal of Signal Processing, 2013, 29(1):85-97.
[25] 陈小龙, 关键, 于仕财, 等. 海杂波背景下基于FRFT的多运动目标检测快速算法[J]. 信号处理, 2010, 26(8):1174-1180. Chen Xiaolong, Guan Jian, Yu Shicai, et al. A fast detection algorithm of multiple moving targets in sea clutter based on FRFT[J]. Journal of Signal Processing, 2010, 26(8):1174-1180.
[26] 陈小龙, 于仕财, 关键, 等. 海杂波背景下基于FRFT的自适应动目标检测方法[J]. 信号处理, 2010, 26(11):1614-1620. Chen Xiaolong, Yu Shicai, Guan Jian, et al. An adaptive detection al-gorithm for moving target at sea in FRFT domain[J]. Journal of Signal Processing, 2010, 26(8):1174-1180.
[27] Tao R, Li Y L, Wang Y. Short-time fractional Fourier transform and its applications[J]. IEEE Transactions on Signal Processing, 2010, 58(5):2568-2580.
[28] 陈小龙, 刘宁波, 王国庆, 等. 基于高斯短时分数阶傅里叶变换的海面微动目标检测方法[J]. 电子学报, 2014, 42(5):971-977. Chen Xiaolong, Liu Ningbo, Wang Guoqing, et al. Gaussian shorttime fractional Fourier transform based detection algorithm of target with micro-motion at sea[J]. Chinese Journal of Electronics, 2014, 42(5):971-977.
[29] Bai X R, Xing M D, Zhou F, et al. Imaging of micromotion targets with rotating parts based on empirical-mode decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(11):3514-3523.
[30] Stankovic L, Thayaparan T, Dakovic M, et al. Micro-Doppler removal in the radar imaging analysis[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(2):1234-1250.
[31] Zhang Q, Yeo T S, Tan H S, et al. Imaging of a moving target with ro-tating parts based on the Hough transform[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(1):291-299.
[32] 王俊, 张守宏. 微弱目标积累检测的包络移动补偿方法[J]. 电子学报, 2000, 28(12):56-59. Wang Jun, Zhang Shouhong. Study on the motion compensation of range migration for weak moving target detection[J]. Chinese Journal of Electronics, 2000, 28(12):56-59.
[33] 霍凯, 黎湘, 姜卫东, 等. 基于分段伪Keystone变换的快速旋转目标检测[J]. 电子学报, 2011, 39(9):2073-2079. Huo Kai, Li Xiang, Jiang Weidong, et al. Fast rotating target detection based on the segmental pseudo Keystone transform[J]. Chinese Journal of Electronics, 2011, 39(9):2073-2079.
[34] Xu J, Xia X G, Peng S B, et al. Radar maneuvering target motion esti-mation based on generalized Radon-Fourier transform[J]. IEEE Trans-actions on Signal Processing, 2012, 60(12):6190-6201.
[35] Yang L S, Zhang Z J, Guo F Y. Fast algorithm for Radon-ambiguity transform[J]. IET Radar, Sonar & Navigation, 2016, 10(3):553-559.
[36] 张天骐, 全盛荣, 强幸子, 等. 基于多尺度Chirplet稀疏分解和Wign-er-Ville变换的时频分析方法[J]. 电子与信息学报, 2017, 39(6):1333-1339. Zhang Tianqi, Quan Shengrong, Qiang Xingzi, et al. Time-frequency analysis method based on multi-scale Chirplet sparse decomposition and Wigner-Ville transform[J]. Journal of Electronics & Information Technology, 2017, 39(6):1333-1339.
[37] Su J, Tao H H, Xie J, et al. Imaging and Doppler parameter estima-tion for maneuvering target using axis mapping based coherently inte-grated cubic phase function[J]. Digital Signal Processing, 2017, 62:112-124.
[38] Chen X L, Guan J, Liu N B, et al. Maneuvering target detection via Radon-fractional Fourier transform-based long-time coherent integra-tion[J]. IEEE Transaction on Signal Processing, 2014, 62(4):939-953.
[39] Chen X L, Guan J, Liu N B, et al. Detection of a low observable seasurface target with micromotion via the Radon-linear canonical trans-form[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(7):1225-1229.
[40] Li X L, Cui G L, Yi W, et al. A fast maneuvering target motion param-eters estimation algorithm based on ACCF[J]. IEEE Signal Processing Letters, 2015, 22(3):265-269.
[41] Guan J, Liu N B, Huang Y, et al. Fractal poisson model for detecting target within spiky sea clutter[J]. IEEE Geoscience & Remote Sensing Letters, 2013, 10(2):411-415.
[42] Luo F, Zhang D T, Zhang B. The fractal properties of sea clutter and their applications in maritime target detection[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(6):1295-1299
[43] 关键, 刘宁波, 宋杰, 等. 分形理论在目标检测中应用[J]. 现代雷达, 2012, 34(2):12-18. Guan Jian, Liu Ningbo, Song Jie, et al. Application of target detection based on fractal theories[J]. Modern Radar, 2012, 34(2):12-18.
[44] 刘宁波, 关键, 王国庆, 等. 基于海杂波FRFT谱多尺度Hurst指数的目标检测方法[J]. 电子学报, 2013, 41(9):1847-1853. Liu Ningbo, Guan Jian, Wang Guoqing, et al. Target detection within sea clutter based on multi-scale hurst exponent in FRFT domain[J]. Chinese Journal of Electronics, 2013, 41(9):1847-1853.
[45] Chen X L, Guan J, He Y, et al. Detection of low observable moving target in sea clutter via fractal characteristics in FRFT domain[J]. IET Radar, Sonar and Navigation, 2013, 7(6):635-651.
[46] Donoho D L. Compressed sensing[J]. IEEE Transactions on Informa-tion Theory, 2006, 52(4):1289-1306.
[47] 李刚, 夏向根. 参数化稀疏表征在雷达探测中的应用[J]. 雷达学报, 2016, 5(1):1-7. Li Gang, Xia Xianggen. Parametric Sparse representation and its appli-cations to radar sensing[J]. Journal of Radars, 2016, 5(1):1-7.
[48] Gilbert A C, Indyk P, Iwen M, et al. Recent developments in the sparse Fourier transform:a compressed Fourier transform for big data[J]. IEEE Signal Processing Magazine, 2014, 31(5):91-100.
[49] 仲顺安, 王雄, 王卫江, 等. 稀疏傅里叶变换理论及研究进展[J]. 北京理工大学学报, 2017, 37(2):111-118. Zhong Shunan, Wang Xiong, Wang Weijiang, et al. Recent advances in the sparse Fourier transform[J]. Transactions of Beijing Institute of Technology, 2017, 37(2):111-118.
[50] 陈小龙, 于晓涵, 关键, 等. 基于短时稀疏时频分布的雷达目标微动特征提取及检测方法[J]. 电子与信息学报, 2017, 39(5):1017-1023. Chen Xiaolong, Guan Jian, Yu Xiaohan, et al. Radar micro-doppler signature extraction and detection via short-time sparse time-frequen-cy distribution. JEIT, 2017, 39(5):1017-1023.
[51] Chen X L, Guan J, He Y. High resolution extraction of radar microdoppler signature using sparse time-frequency distribution[C]. 32nd International Union of Radio Science General Assembly and Scientific Symposium (URSI 2017 GASS), Montréal, August 19-26, 2017.
[52] Chen X L, Yu X H, Guan J, et al. High-resolution sparse representa-tion of micro-doppler signal in sparse fractional domain[C]. The 2nd EAI International Conference on Machine Learning and Intelligent Communications (MLICOM 2017), Weihai, August 5-6, 2017.
[53] 何友, 王国宏, 陆大琻, 等. 多传感器信息融合及应用[J]. 北京:电子工业出版社, 2010. He You, Wang Guohong, Lu Dajin, et al. Multi sensor information fu-sion and its application[M]. Beijing:Publishing House of Electronics, 2010.
[54] 何友, 王国宏, 关欣, 等. 信息融合理论及应用[J]. 北京:电子工业出版社, 2010. He You, Wang Guohong, Guan Xin, et al. The information fusion theo-ry and application[M]. Beijing:Publishing House of Electronics, 2010.
[55] 余凯, 贾磊, 陈雨强, 等. 深度学习的昨天、今天和明天[J]. 计算机研究与发展, 2013, 50(9):1799-1804. Yu Kai, Jia Lei, Chen Yuqiang, et al. Deep learning:Yesterday, to-day, and tomorrow[J]. Journal of Computer Research and Develop-ment, 2013, 50(9):1799-1804.
[56] 周志文, 黄高明, 高俊, 等. 一种深度学习的雷达辐射源识别算法[J]. 西安电子科技大学学报, 2017, 44(3):77-82. Zhou Zhiwen, Huang Gaoming, Gao Jun, et al. Radar emitter identifi-cation algorithm based on deep learning[J]. Journal of Xidian Universi-ty, 2017, 44(3):77-82.
[57] 徐丰, 王海鹏, 金亚秋. 深度学习在SAR目标识别与地物分类中的应用[J]. 雷达学报, 2017, 6(2):136-148. Xu Feng, Wang Haipeng, Jin Yaqiu. Deep learning as applied in SAR target recognition and terrain classification[J]. Journal of Radars, 2017, 6(2):136-148.
[58] 杨建宇. 雷达技术发展规律和宏观趋势分析[J]. 雷达学报, 2012, 1(1):19-27. Yang Jianyu. Development laws and macro trends analysis of radar technology[J]. Journal of Radars, 2012, 1(1):19-27.
[59] 焦李成, 杨淑媛, 刘芳, 等. 神经网络七十年:回顾与展望[J]. 计算机学报, 2016, 39(8):1697-1716. Jiao Licheng, Yang Shuyuan, Liu Fang, et al. Seventy years beyond neural networks:Retrospect and prospect[J]. Chinese Journal of Com-puters, 2016, 39(8):1697-1716.
