姓名：张玲
职称/职务：教授、博导
专业：自动化
实验室：智能信息处理实验室
所在单位（系、所、中心等）：工程学院自动化及测控系
通讯地址：青岛市黄岛区古镇口核心区三沙路1299号中国海洋大学工程学院266500
学习经历：
1.2003.9-2007.7 清华大学 控制科学与工程专业 博士学位
2.2000.9-2003.7 中国海洋大学 信号与信息处理专业 硕士学位
3.1996.9-2000.7 中国海洋大学 自动化专业 学士学位
工作经历：
2007.7-至今 中国海洋大学工程学院自动化及测控系 教师
2017.6-2018.7 加拿大温莎大学University of Windsor访问学者，合作教授为加拿大工程院院士武庆明首席科学家
研究方向：
智能信息处理、通信信号处理、模式识别、机器学习
讲授课程：
1.本科生课程： 《信号与系统》，《系统辨识》
2.研究生课程： 《矩阵分析》（基础必修课）、《最优估计理论》
科研项目：
国家自然科学基金：复杂影响因素下船载地波雷达杂波掩盖目标精确探测方法研究，主持
国家重点研发计划：面向进出港船舶安全智控的海港水域数字孪生工程原理，子课题负责人
国家自然科学基金项目：基于深度学习的地波雷达杂波干扰内目标智能检测方法研究，主持
国家自然科学基金项目：基于弧段检测的高频地波雷达特定目标航迹跟踪方法研究，主持
山东省自然科学基金项目：水声通信系统多参数联合自适应估计方法研究，主持
国家自然科学基金项目：无人船平台动态接入海床基观测网及数据回收研究，校内主持
国家基金重点项目：船载高频地波超视距雷达海洋动力过程遥测技术基础研究，参与
公益性行业科研专项：海上船只目标星-机-岛立体监视监测技术系统，参与
所获奖励：
Ø2025年，指导本科生一作发表高水平论文
Ø2024年，山东省自动化学会科学技术奖自然科学奖（张嗣瀛奖）
Ø2023年，中国海洋大学教师教学创新大赛二等奖
Ø多次被评为优秀班主任
Ø多次被评为本科毕业论文优秀指导教师
Ø中国海洋大学第十二届优秀教材奖
Ø获第十二届全国大学生“恩智浦”杯智能汽车竞赛优秀指导教师奖；指导的多个队伍获得全国、山东省和青岛市竞赛一等奖
Ø2014年，获第七届山东省高等教育教学成果奖二等奖
Ø2010年,荣获中国海洋大学第八届优秀教学成果奖二等奖
Ø第十七届中国海洋大学大学生科技成果表彰“优秀指导教师”
Ø山东省机器人大赛高校组比赛中，荣获指导奖二等奖
Ø近五年指导大学生智能车队伍获国家一、二等奖6项、省级一、二等奖20余项
Ø连年被评为山东省大学生智能汽车竞赛“优秀指导教师”
Ø青岛市大学生智能汽车竞赛优秀指导教师
Ø第四届全国海洋航行器设计与制作大赛和山东省高校机器人大赛赛务组织“优秀工作者”
学术兼职：
中国海洋湖沼学会信息技术专业委员会会员
IEEE Trans. Cybernetics, IEEE Trans. Control Systems Technology, IEEETGRS，IEEE TMM等知名期刊审稿人
国际交流：
实验室具有良好的国际交流氛围和前沿学术视野，与加拿大武庆明院士在学术研究、实验室建设、研究生培养等方面保持长期深入的实质合作，研究生具有扎实的知识基础、开阔的国际视野和多元交融的创新能力。
代表性论著
部分论文:
[1]Yaolong Lu, et al. Orthogonal momentum progressive subnetwork representation learning with feature fusion for surface wave radar target detection, Engineering Applications of Artificial Intelligence, 2026(学生一作)
[2]Cheng Wang, et al. Shipborne HFSWR Target Detection via Multi-Frame Morphological–Temporal Feature Fusion, IEEE Transactions on Aerospace and Electronic Systems, 2026. doi: 10.1109/TAES.2026.3737365. (学生一作)
[3]Xu Sun, Ling Zhang, et al. Path planning algorithm for unmanned surface vessels based on COLREGs and Meta-TD3, Ocean Engineering, Vol. 334, 2025, 121580, ISSN 0029-8018, https://doi.org/10.1016/j.oceaneng.2025.121580. (学生一作)
[4]Ben Li, et al. Dynamic DOA Estimation Error Correction for Shipborne HFSWR under 6-DOF Motion, IEEE Transactions on Aerospace and Electronic Systems, vol. 62, pp. 5183-5198, 2026, doi: 10.1109/TAES.2026.3660645. (学生一作)
[5]Cheng Wang, Ling Zhang, et al. Accurate Direction Finding for Shipborne HFSWR Through Platform Motion Compensation, IEEE Transactions on Geoscience and Remote Sensing, 2023, DOI: 10.1109/TGRS.2023.3328264 (学生一作)
[6]Kaixian Yang, Ling Zhang, et al. Analysis and Estimation of Shipborne HFSWR Target Parameters Under the Influence of Platform Motion, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 6, pp. 4703-4716, June 2021, doi: 10.1109/TGRS.2020.3023025. (学生一作，国奖获得者)
[7]Maokai Wu, Ling Zhang, et al. Target Detection in Clutter/Interference Regions Based on Deep Feature Fusion for HFSWR, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 5581-5595, 2021, doi: 10.1109/JSTARS.2021.3082044. (学生一作，国奖获得者)
[8]Ling Zhang, Dongwei Mao, et al. Continuous Tracking of Targets for Stereoscopic HFSWR Based on IMM Filtering Combined with ELM. Remote Sensing, 2020, 12, 272.(学生通讯，国奖获得者)
[9]XuSun, Ling Zhang, et al. A novel path planning method for multiple USVs to collect seabed-based data, Ocean Engineering, 269, 2023 (学生一作)
[10]Zongtai Li, et al. A Multi-Stage Detection Framework Based on TFA and Multiframe Correlation for HFSWR, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025. DOI: 10.1109/JSTARS.2025.3527468 (学生一作)
[11]Jiangnan Zhong, et al. Shipborne HFSWR Target Detection in Sea Clutter Regions Based on 3D Feature Fusion, IEEE Transactions on Radar Systems, doi: 10.1109/TRS.2024.3472075. (学生一作)
[12]Tao Wang, Ling Zhang, et al. Shipborne HFSWR Target Detection in Clutter Regions Based on Multi-Frame TFI Correlation. Remote Sensing, 2022, 14(17), 4192: 1-16. (学生一作)
[13]Cheng Wang, et al. Shipborne HFSWR direction-finding method for target detection based on correction matrix, IEEE Geoscience and Remote Sensing Letters, vol. 22, pp. 1-5, 2025, Art no. 3501005. doi: 10.1109/LGRS.2024.3514873 (学生一作)
[14]Jingzhi Zhang, et al. Track Prediction for HF Radar Vessels Submerged in Strong Clutter Based on MSCNN Fusion with GRU-AM and AR Model. Remote Sensing. 2021; 13(11):2164. https://doi.org/10.3390/rs13112164 (学生一作)
[15]Ling Zhang, Chenlu Shi, et al. DOA Estimation for HFSWR Target Based on PSO-ELM, IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 3504205, doi: 10.1109/LGRS.2021.3062373. (学生通讯)
[16]Mingyang Li, Ling Zhang, et al. Optimal Estimation for Systems with Multiplicative Noises, Random Delays and Multiple Packet Dropouts. IET Signal Processing, 2016, 10(8):880-887(学生一作)
[17]Ling Zhang, Qingfeng Li, et al. Target detection for HFSWR based on an S3D algorithm, IEEE Access, vol. 8, 224825-224836, 2020. (学生通讯，国外大学交流学习一年)
出版的译注/教材:
译著：《ModernSignalProcessing》，De Gruyter, 2022
教材：《“飞思卡尔”杯智能车设计与实践》，北京航空航天大学出版社，2015
专利：
1.一种基于双查找表方法的高频地波雷达测向新方法，国家发明专利，授权日：2020.10.30，专利号：ZL201710819351.9
2.一种地波雷达船只断裂航迹预测方法，专利号：202110027736.8，授权日：2023.2.6，
3.软件著作权：《信号与系统》课程实验——信号运算软件, 编号：2020R11S1140472, 登记号2020SR1265441
Resume in English
Ling Zhang
Title: Professor, Ph.D.advisor
Department: Department of Automation
Lab: Intelligent signal processing laboratory
E-mail：zljoan@163.com
Education
1.2003.9-2007.7 PhD of control science and engineering, Tsinghua University
2.2000.9-2003.7 Master’s degree of Signal and Information Processing,
Ocean University of China
3.1996.9-2000.7 Bachelor’s degree of Automation, Ocean University of China
Work Experience
2007.7–Now Teaching at College of Engineering, Ocean University of China
2017.6-2018.7 Visiting scholar at University of Windsor, Canada
Research Interests
Intelligent information processing, Communication signal processing, Pattern recognition, Machine learning
Courses
Signals and Systems, System Identification, Optimal Estimation Theory, Matrix Analysis
Research Projects
ØNational Natural Science Foundation of China:
Research on accurate detection method of shipborne HFSWR targets concealed in clutter under complex influence factors
ØNational Key Research and Development Program Project
Principles of digital twin engineering for safe and intelligent control of harbor waters for inbound and outbound ships
ØNational Natural Science Foundation of China:
Deep learning-based intelligent detection of vessel targets concealed in clutter/interference for HFSWR
ØNational Natural Science Foundation of China:
Research on Specific Target Tracking Method Based on Arc Detection with HF Surface Wave Radar
ØNatural Science Foundation of Shandong Province:
Research on adaptive jointestimationofmulti-parameters for underwateracousticcommunication systems
ØNational Natural Science Foundation of China:
Data collection and dynamic accessing for a network of sea bottom mountings by an unmanned surface vehicle
ØState Key Program of National Natural Science Foundation of China:
Research on remote sensing technology for ocean dynamics based on shipborne HFSWR
ØNational Marine Technology Program for Public Welfare:
Satellite-airplane-island based three-dimensional ship monitoring system
Rewards
Ø2024, Second prize of Natural Science Award of Shandong Automation Society
Ø2023，Second prize of teachers' teaching innovation competition at OUC
Ø2020, Excellent instructor of undergraduate thesis
Ø2018, Excellent textbook award
Ø2014, Second prize in 7th education and teaching award of college education of Shandong
Ø2016，Outstanding advisor in undergraduate thesis
Ø2010, Second prize in 8th education and teaching award of Ocean University of China
Ø“Excellent instructor” in 17th award of scientific and technological achievements of Ocean University of China for college students
ØSecond prize of instructor awards in college group of the Robot Contest of Shandong
ØGuided several national and over 20 provincial awards of NXP smart car competition
Ø“Excellent instructor” in NXP smart car competition of Shandong province
Ø“Excellent instructor” in Qingdao city college students smart car competition
Ø“Excellent worker” in the 4th national marine craft design and manufacture contest
ØExcellent Class Adviser
