刘升恒

时间:2018-11-29浏览:3522

职称:副教授/硕导

办公室:南京市江宁区秣周东路9号中国无线谷A5-215

办公电话:

Email s.liu@seu.edu.cn

学习经历:

 2006.092010.06北京理工大学信息与电子学院本科生(保送本直博)

 2010.092017.03北京理工大学信息与电子学院博士研究生

 2015.102016.10美国天普大学(Temple University) 国家公派联合培养博士生

工作经历:

● 2017.04—2018.08英国爱丁堡大学(The University   of Edinburgh) 博士后

● 2018.09—至今东南大学信息科学与工程学院副教授(硕士生导师)

教授课程:

《无源雷达探测中的信号处理(双语研讨)》本科三年级(春季)专业选修课

《数字通信原理与系统》研究生一年级(春季)专业必修课

研究方向:

智能传感探测

智能无线通信

信号处理理论

雷达信号处理

* 更多信息详见个人主页:https://sites.google.com/site/shenghengliu/

获奖情况:

 2017年度中国通信学会优秀博士学位论文奖

论文著作:

部分期刊论文:

[J1]   Liu, S., Huang, Y., Wu, H., Tan, C., Jia, J., ‘Efficient multi-task structure-aware sparse Bayesian learning   for frequency-difference electrical impedance tomography’, IEEE   Transactions on Industrial Informatics, vol. 16, no. 10, in press,   (DOI: 10.1109/TII.2020.2965202), Oct. 2020.

[J2]   Liu, S., Cao, R., Huang, Y., Ouypornkochagorn, T., Jia, J.,   ‘Time Sequence Learning for Electrical Impedance Tomography Using Bayesian   Spatiotemporal Priors’, IEEE Transactions on Instrumentation and   Measurement, vol. 69, in press, (DOI: 10.1109/TIM.2020.2972172),   2020.

[J3]   Liu, S., Wu, H., Huang, Y., Yang, Y., and Jia, J.,   ‘Accelerated structure-aware sparse Bayesian learning for three-dimensional   electrical impedance tomography’, IEEE Transactions on Industrial   Informatics, vol. 15, no. 9, pp. 5033–5041, Sept.   2019.

[J4]   Liu, S., Ma, Y., and Huang, Y., ‘Sea clutter cancellation   for passive radar sensor exploiting multi-channel adaptive filters’, IEEE   Sensors Journal, vol. 19, no. 3, pp. 982–995, Feb.   2019.

[J5]   Liu, S., Jia, J., Zhang, Y.D., and Yang, Y., ‘Image reconstruction   in electrical impedance tomography based on structure-aware sparse Bayesian   learning’, IEEE Transactions on Medical Imaging, vol. 37,   no. 9, pp. 2090–2102, Sept. 2018.

[J6]   Liu, S., Zhang, Y.D., Shan, T., and Tao, R.,   ‘Structure-aware Bayesian compressive sensing for frequency-hopping spectrum   estimation with missing observations’, IEEE Transactions on Signal   Processing, vol. 66, no. 8, pp. 2153–2166, Apr.   2018.

[J7]   Liu, S., Shan, T., Tao, R., Zhang, Y.D., Zhang, G., Zhang,   F., and Wang, Y., ‘Sparse discrete fractional Fourier transform and its   applications’, IEEE Transactions on Signal Processing, vol.   62, no. 24, pp. 6582–6595, Dec. 2014.

[J8] Liu,   S., Zhang, Y.D., and Shan, T., ‘Detection of weak astronomical   signals with frequency-hopping interference suppression’, Digital   Signal Processing, vol. 72, pp. 1–8, Jan. 2018.

[J9]   Shan, T., Liu, S., Zhang, Y.D., Amin, M.G., Tao, R.,   and Feng, Y., ‘Efficient architecture and hardware implementation of coherent   integration processor for digital video broadcast-based passive bistatic   radar’, IET Radar Sonar and Navigation, vol. 10,   no. 1, pp. 97–106, Jan. 2016.

[J10]   Shan, T., Liu, S., Tao, R., and Zhang, G., ‘Experiment   demonstration of micro-Doppler detection of rotor blades with passive   coherent location based on digital video broadcast’, Journal of   Communications Technology and Electronics, Springer, vol. 59,   no. 11, pp. 1215–1224, Nov. 2014.

[J11] Liu,   S., Shan, T., Tao, R., and Wang, Y., ‘Liveness evaluation of   multi-living agent system’, Journal of Systems Engineering and   Electronics, vol. 24, no. 3, pp. 435–444, June   2013.

[J12]Pang,   C., Liu, S., and Han, Y., ‘Coherent detection algorithm   for radar maneuvering targets based on discrete polynomial-phase   transform’, IEEE Journal of Selected Topics in Applied Earth   Observations and Remote Sensing, vol. 12, no. 9,   pp. 3412–3422, Sept. 2019.

[J13]Pang,   C., Liu, S., and Han, Y., ‘High-speed target detection   algorithm based on sparse Fourier transform’, IEEE Access, vol.   6, pp. 37828–37836, July 2018.

  

部分会议论文:

[C1] Liu, S., Ma, Y., and Shan, T.,   ‘Segmented discrete polynomial-phase transform with coprime sampling’,   Presented at the 2018 IET International Radar Conference (IRC), art. no. C0073,   Nanjing, China, October 17–19, 2018.

[C2] Liu, S., Jia, J., and Yang, Y., ‘Image   reconstruction algorithm for electrical impedance tomography based on block   sparse Bayesian learning’, Presented at the 2017 IEEE International   Conference on Imaging Systems and Techniques (IST 2017), pp. 267–271,   Beijing, China, October 18–20, 2017.

[C3] Liu, S., Zhang Y.D., and Shan, T.,   ‘Sparsity-based frequency-hopping spectrum estimation with missing samples’,   Presented at the 2016 IEEE Radar Conference, pp. 1043–1047, Philadelphia, PA,   USA, May 2–6, 2016.

[C4] Liu, S., Zhang Y.D., Shan, T., Qin,   S., and Amin, M.G., ‘Structure-aware Bayesian compressive sensing for   frequency-hopping spectrum estimation’, Presented at the 2016 SPIE Defense +   Commercial Sensing, art. no. 98570N, Baltimore, MD, USA, April 17–21, 2016.

[C5] Liu, S., Zeng, Z., Zhang Y.D., Fan,   T., Shan, T., and Tao, R., ‘Automatic human fall detection in fractional   Fourier domain for assisted living’, Presented at the 41st IEEE International   Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), pp.   799–803, Shanghai, China, March 20–25, 2016.

[C6] Liu, S., Shan, T., Zhang Y.D., Tao,   R., and Feng, Y., ‘A fast algorithm for multi-component LFM signal analysis   exploiting segmented DPT and SDFrFT’, Presented at the IEEE International   Radar Conference, pp. 1139–1143, Arlington, VA, USA, May 11–15, 2015.

[C7] Liu, S., and Jia, J., ‘Sequential EIT   frame reconstruction exploiting spatiotemporal correlation’, Presented at the   19th International Conference on Biomedical Applications of Electrical   Impedance Tomography (EIT), p. 44, Edinburgh, UK, June 11–13, 2018.

[C8] Liu, S., and Jia, J., ‘EIT velocity   field estimation via pixel-to-pixel least-squares matching’, Presented at the   ISIPT 9th World Congress on Industrial Process Tomography (WCIPT), Bath, UK, art.   no. P002, September 2–6, 2018.

[C9] Zheng, C., Liu, S., Huang, Y., and Yang, L., ‘MEC-enabled   wireless VR video service: A learning-based mixed strategy for energy-latency   tradeoff’, Accepted by the 2020 IEEE Wireless Communications and Networking   Conference (WCNC), Seoul, South Korea, April 6–9, 2020.

[C10] Ma, Y., Liu, S., and Lu, J., ‘A multi-channel   partial-update algorithm for sea clutter suppression in passive bistatic   radar’, Presented at the 2018 IEEE Sensor Array and Multichannel Signal   Processing (SAM) Workshop, pp. 252–256, Sheffield, UK, July 8–11, 2018.

[C11] Ren, D.,   Chen, K., Liu, S., and   Huang, Y., ‘FPGA prototyping of a China millimeter-wave multiple gigabit WLAN   system’, Accepted by the 2019 IEEE International Workshop on Signal   Processing Systems (SiPS), art. no. 6, Nanjing, China, October 20–23, 2019.

  

科研项目:

项目名称

项目类别

项目时间

工作类别

项目金额

稀疏分数傅里叶变换及其应用研究

国家自然科学基金项目

2017.01-2020.12

主要参与人

60万元

Cerebral blood flow imaging based on 3D electrical impedance   tomography

英国EPSRC项目

2017.02-2018.05

主要参与人

10万英镑

基于框架提升变换的多源图像融合研究

国家自然科学基金项目

2016.01-2018.12

主要参与人

22.8万元

基于多维特征学习的电阻抗层析成像与识别研究

江苏省自然科学基金项目

2019.07-2022.06

主持

20万元

5G场景下波束设计和特定信号探测

国家自然科学基金项目

2020.01-2023.12

主要参与人

260

数据与模型协同驱动的智能边缘传输网络

国家重点研发计划项目子课题

2019/07-2023/06

主要参与人

573

专利:

专利号

专利名称

专利类型

201210283226.8

一种基于数字电视信号的直升机目标识别方法

授权发明专利

201310227099.4

基于子带处理的宽带信号目标检测多普勒色散消除方法

授权发明专利

201310240881.X

一种直达波及其多径干扰的抑制方法

授权发明专利

201310240140.1

一种利用稀疏傅里叶变换计算外辐射源雷达互模糊函数的方法

授权发明专利

201410161409.1

一种基于频域相位校正的外辐射源雷达距离徙动补偿方法

授权发明专利