| 职称：副教授、博导 | |||
办公室：四牌楼健雄院311 | ||||
办公电话：025-83794074 | ||||
Email：qisong.wu@seu.edu.cn | ||||
学习经历： | ||||
2001年9月-2005年7月西安电子科技大学电子工程学院本科 2005年9月-2006年7月西安电子科技大学电子工程学院硕士 2006年9月-2010年6月西安电子科技大学电子工程学院博士 | ||||
工作经历: | ||||
2010年12月-2013年5月美国杜克大学电子与计算机工程博士后 2013年5月-2015年5月美国维拉诺瓦大学高级通信研究中心博士后研究员 2015年7月-至今 东南大学信息科学与工程学院副教授 | ||||
教授课程： | ||||
本科大三课程（秋季）：雷达前沿技术：预警和成像 本科大三课程（秋季）：数字信号处理 研究生课程（春季）：统计信号处理 | ||||
研究方向： | ||||
声呐信号处理领域：舰船目标特征提取和识别技术，阵列信号处理，宽带波束形成等 机器学习和模式识别领域：贝叶斯压缩感知理论，非参数贝叶斯分析，贝叶斯分层模型设计等 雷达信号处理领域：毫米波雷达信号处理，合成孔径雷达成像（SAR），穿墙雷达成像，无源雷达成像、(SAR-GMTI)运动目标检测等 | ||||
获奖情况： | ||||
1 高等学校优秀科研成果奖：教育部科技进步一等奖，2018 2 全国高校大数据应用创新大赛全国总决赛二等奖（指导教师），2018 3 江苏省青年声学科技工作者科技奖，2020 | ||||
论文著作： | ||||
在IEEE Transaction on Geoscience and Remote Sensing (T-GRS), IEEE Transaction on Biomedical Engineering (T-BE), IEEE Transaction on Aerospace and Electronic Systems（IEEE TAES）, IEEE Journal of Selected Topics in Signal Processing（J-STSP）, IEEE Signal Processing Letters (SPL), IEEE Geoscience and Remote Sensing Letters (GRSL)等期刊及国际会议发表SCI/EI收录学术论文70余篇、引用次数近1200余次，H-index为16。长期担任IEEE Transactions on Signal Processing (IEEE TSP), IEEE T-GRS,IEEE J-STSP, IEEE SPL, IEEE GRSL, SP等期刊审稿。 [1] Qisong Wu, Z Lai, MG Amin. Through-the-wall radar imaging based on Bayesian compressive sensing exploiting multipath and target structure. IEEE Transactions on Computational Imaging, vol. 7, 2021, 422-435. [2] Qisong Wu, H Zhang, Z Lai, Y Xu, S Yao, J Tao. An enhanced data-driven array shape estimation method using passive underwater acoustic data. Remote Sensing, vol. 13, no.9, 1773, 2021. [3] J. Liu, Qisong Wu*, M.G. Amin. Multi-Task Bayesian compressive sensing exploiting signal structures. Signal Processing, 178,107804, 2021 [4] Qisong Wu, J. Liu, M.G. Amin. Group adaptive matching pursuit with intra-group correlation learning for sparse signal recovery. Signal Processing, 172,107560, 2020. [5] Qisong Wu, S. Fang, Structured Bayesian compressive sensing with spatial location dependence via variational Bayesian inference, Digital Signal Processing, 71, 2017, pp. 95-107. [6] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed. Space–Time Adaptive Processing and Motion Parameter Estimation in Multistatic Passive Radar Using Sparse Bayesian Learning, IEEE Transactions on Geoscience and Remote Sensing, Vol. 54, No.2, 2016, pp. 944-957. [7] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed. High-Resolution Passive SAR Imaging Exploiting Structured Bayesian Compressive Sensing. IEEE Journal of Selected Topics in Signal Processing, Vol.9, No.8, 2015, pp.1484-1497. [8] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed. Multi-Task Bayesian Compressive Sensing Exploiting Intra-Task Dependency. IEEE Signal Processing Letter, Vol 22, No. 4, 2015. [9] Qisong Wu, Y. Zhang, M. G. Amin and F. Ahmad. Compressive Sensing Based High-Resolution Polarimetric Through-the-Wall Radar Imaging Exploiting Target Characteristics, IEEE Antennas and Wireless Propagation Letters, 14, 2015, pp.1043-1047. [10] Qisong Wu, Y. Zhangand M. G. Amin. Radar-based fall detection based on Doppler time–frequency signatures for assisted living. IET Radar, Sonar & Navigation , Vol. 9, No.2, 2015. 部分会议论文 [1] Z Mei, Qisong Wu*, Z Hu, J Tao. A Fast Non-Contact Vital Signs Detection Method Based on Regional Hidden Markov Model in A 77ghz Lfmcw Radar System. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020. [2] T Gao, Z Lai, Z Mei, Qisong Wu*. Hybrid SVM-CNN classification technique for moving targets in automotive FMCW radar system. International Conference on Wireless Communications and Signal Processing (WCSP), 2019. [4] J Liu, Qisong Wu*, Y. D Zhang. Multi-task Adaptive Matching Pursuit for Sparse Signal Recovery Exploiting Signal Structures. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019. [5] Qisong Wu, P Xu, S Fang. Reconstruction of Radiated Noise Demodulation Spectrum by Exploiting the Structure of Group Sparsity. INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 2018. [6] Qisong Wu, P Xu, T Li, S Fang. Feature Enhancement Technique with Distorted Towed Array in the Underwater Radiated Noise. INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 2017. [7] Qisong Wu. High-Resolution DOA Estimation in the underwater radiated noise based on Sparse Bayesian Learning, INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 2016. [8] Qisong Wu, Yimin D Zhang, Moeness G Amin, Fauzia Ahmad. Autofocus Bayesian compressive sensing for multipath exploitation in urban sensing. IEEE International Conference on Digital Signal Processing (DSP), 2015. [9] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed.Space-Time Adaptive Processing in Multi-static Passive Radar Exploiting Group Sparsity. IEEE International Radar Conference, 2015. [10] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed. Structured Bayesian Compressive Sensing. IEEE ICASSP, 2014. [11] Qisong Wu, Y. Zhang, Moeness G. Amin and Braham Himed. Complex Multi-task Bayesian Compressive Sensing, ICASSP, Florence, Italy, 2014. [12] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed.Focusing of Tandem Bistatic SAR Data Using Range Doppler Algorithm. IEEE Radar Conference, Cincinnati, Ohio, USA, 2014. [13] Qisong Wu, Y. Zhang, M. G. Amin and Braham Himed. High-Resolution Passive SAR Imaging Exploiting Complex Group Sparse Bayesian Learning. SPIE Conference, Baltimore, MD, USA, 2014. [14] Qisong Wu, Y. Zhang, M. G. Amin and Fauzia Ahmad. Through-The-Wall Radar Imaging Based on Modified Bayesian Compressive Sensing. IEEE ChinaSIP Conference, Xi’an China, 2014. [15] Qisong Wu, Y. Zhang, M. G. Amin and Fauzia Ahmad. Robust Multipath Exploitation Radar Imaging in Urban Sensing Based on Bayesian Compressive Sensing, Asilomar Conference, CA, USA, 2014. [16] Qisong Wu, Y. Zhang, M. G. Amin, Andrew Golato, Sridhar Santhanam, Fauzia Ahmad. Structure Health Monitoring Exploiting MIMO Ultrasonic Sensing and Group Sparse Bayesian Learning. Asilomar Conference, CA, USA, 2014. [17] Qisong Wu, Y. Zhang and M. G. Amin. Continuous Structure Based Bayesian Compressive Sensing for Sparse Reconstruction of Time-Frequency Distributions, Digital Signal Processing Conference, HongKong, China, 2014. | ||||
科研项目： | ||||
项目名称 | 项目类别 | 项目时间 | 工作类别 | 项目金额 |
XXXX识别技术研究 | 重点领域基金 | 2019-2022 | 应用基础研究 | XX万 |
XXXX平台技术研究 | 创新团队 | 2020-2024 | 应用基础研究 | XX万 |
XXXX测试技术研究 | 重大科技专项 | 2019-2021 | 应用基础研究 | XX万 |
基于XXXX识别技术研究 | 预研基金 | 2019-2020 | 应用基础研究 | XX万 |
XXXX特征增强技术研究 | 基础科研基金 | 2019-2021 | 应用基础研究 | XX万 |
XXXX判别技术研究 | 预研基金 | 2017-2020 | 应用基础研究 | XX万 |
XXXX综合处理研究 | 预研基金 | 2017-2020 | 应用基础研究 | XX万 |
XXXX技术研究 | 预研基金 | 2017-2020 | 应用基础研究 | XX万 |
基于XXXX雷达成像技术 | 国家自然科学基金 | 2018-2020 | 应用基础研究 | XX万 |
基于XXXX目标DOA估计 | 江苏省自然科学基金 | 2016-2018 | 应用基础研究 | XX万 |
基于XXXX估计技术研究 | 基础研究基金 | 2017-2018 | 应用基础研究 | XX万 |
XXX提取技术研究 | 预研项目 | 2016-2020 | 应用基础研究 | XX万 |
XXXX识别技术 | 预研加强项目 | 2016-2017 | 应用基础研究 | XX万 |
Signal processing for improved multi-static passive radar moving target detection, localization and imaging | Air Force Research Laboratory (AFRL) | 2013-2015 | 应用基础研究 | XX万 |
Multipath exploitation and knowledge based urban radar imaging using compressive sensing | Army Research Office/ Army Research Laboratory | 2014-2015 | 应用基础研究 | XX万 |
Development of nonparametric statistical model for analysis of neural data | Defense Advanced Research Projects Agency (DARPA） | 2011-2013 | 应用基础研究 | XX万 |
专利： | ||||
专利号 | 专利名称 | 专利类型 | ||
201810669600.5 | 一种基于卷积神经网络的水下目标识别方法 | 发明专利申请 | ||
201810199933.6 | 一种基于卷积神经网络的毫米波传感器手势识别 | 发明专利申请 | ||
201810364540.6 | 一种基于组稀疏结构的水声目标辐射噪声调制谱重构方法 | 发明专利申请 | ||
201811308366.X | 一种基于组稀疏的自适应匹配追踪信号重建算法 | 发明专利申请 | ||
201910601880.0 | 基于车载毫米波雷达联合SVM和CNN多目标分类方法 | 发明专利申请 | ||
201910489514.0 | 一种基于车载毫米波雷达的多目标分类方法 | 发明专利申请 | ||
201910875693.1 | 一种基于线谱跟踪的生命信号特征提取方法 | 发明专利申请 | ||
201911219659.5 | 一种畸变拖曳阵线谱特征增强方法及系统 | 发明专利申请 | ||
