老师简介

朱洪艳

女,教授,博士生导师,黑龙江省牡丹江人。

研究领域或方向

统计信号处理、多源信息融合、语音信号处理、多目标跟踪、传感器管理。

教育经历

1996 西安交通大学理学院,计算数学学士;

1999 西安交通大学理学院,计算数学硕士;

2003 西安交通大学电信学院,控制科学与工程博士。

工作简历

1999年4月至2005年11月,西安交通大学电信学院,讲师;

2005年12月至2014年12月,西安交通大学电信学院,副教授;

2009年5月至2010年2月,澳大利亚墨尔本大学,访问学者;

2015年10月至2016年10月,美国俄克拉荷马州立大学,访问学者;

2015年1月至今,西安交通大学电信学院,教授、博士生导师。

科研项目

主持或作为骨干成员参与多项国家重点基础研究发展规划(973计划)项目课题、国家自然科学基金项目、以及研究所横向委托项目。

  • 国家自然科学基金
    项目名称:基于分布式量化量测的多传感联合检测和估计融合理论研究(61673313)

  • 国家自然科学基金
    项目名称:基于复杂强度分布量测随机集模型的扩展目标跟踪方法研究(61203220)

  • **研究所横向课题
    项目名称:信息融合技术研究与软件开发

  • **研究所横向课题
    项目名称:无人机辅助定位系统

  • **研究所横向课题
    项目名称:光电信息感知系统之航迹处理系统

  • **高校横向课题
    项目名称:抗差航迹关联技术研究

  • 国家重点研究和发展规划 (973项目)
    项目名称:基于多源异构信息融合的空中目标跟踪关键技术

  • 国家重点研究和发展规划(973项目)
    项目名称:基于联合决策与估计的目标信息处理及其在群目标识别与跟踪中的应用

  • 高校基本科研业务费(自由探索类)
    项目名称:基于随机有限集理论的扩展目标建模与跟踪方法研究

  • 高校基本科研业务费(综合交叉类)
    项目名称:基于传感器选择的鲁棒航迹融合问题研究

学术及科研成果

(1)韩崇昭,朱洪艳 , 段战胜.《多源信息融合》,清华大学出版社,2006.

(2)杨清宇,马训明,朱洪艳. 《现代控制理论》,西安交通大学出版社,2013.

获奖

  • 专著《多源信息融合》(排名第二)入选国家新闻出版总署首届“三个一百”自然科学类原创出版工程;

  • “基于异构信息融合的非线性动态系统估计技术及应用” 获2011年度国家科技进步二等奖(排名第四);

  • “基于多源异构信息融合的多目标跟踪理论、技术与应用系统”获2010年度教育部科技进步一等奖(排名第三)。

主要任职

  • 国际信息融合学会委员

  • 中国航空学会信息融合分会委员

  • 陕西省自动化学会控制理论与应用专业委员会委员

  • 国际信息融合会议技术程序委员会委员

  • 2017国际信息融合会议Local Arrangements and Exhibitions Co-Chairs

  • 2017国际信息融合会议分会场主席

  • 2015,2017中国控制会议分会场主席

  • IEEE会员、国际信息融合学会(ISIF)会员

  • 担任《IEEE Trans. on AES》, 《Information Fusion》,《Digital Signal Processing》,《IET Signal Processing》, 《IET Radar, Sonar& Navigation》, 自动化学报,航空学报等审稿人。

教学

主讲自动化系本科生课程《现代控制理论》、以及研究生课程《多传感信息融合》。

论文

2017

[1] H.Y.Zhu, Z.L.Li, Q.Cheng. Sound Source Localization through Optimal Peak Association in Reverberant Environments. 20th International Conference on Information Fusion Xi'an, China - July 10-13, 2017.

[2] H.Y.Zhu, R.L Sun. Joint Detection and Estimation Fusion in the Presence of Correlated Sensor Quantized Data. 20th International Conference on Information Fusion Xi'an, China - July 10-13, 2017.

[3] G.W.Yang; Q. Cheng, Y. Guo, H.Y.Zhu. Acoustic source tracking using multiple weighted peaks of the localization function. 36th Chinese Control Conference Dalian, China-July 25-28, 2017.

[4] Y.Guo, H.Y.Zhu, Q.Cheng. Indoor Multi-sound Source Localization Based on Nonparametric Bayesian Clustering. 42th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, 5-9 March 2017.


2016


[5] H.Y.Zhu, W.Wang, C.Wang, Robust track-to-track association in the presence of sensor biases and missed detections, Information Fusion, 2016, 27:33–40.

[6] H.Y.Zhu, K.Guo, S.Chen, Fusion of Gaussian Mixture Models for maneuvering target tracking in the presence of unknown cross-correlation, Chinese Journal of Electronics, 2016, 25(2): 270-276.

[7] H.Y.Zhu, P.D.zhang. Joint detection and estimation fusion in distributed multiple sensor systems. 19th International Conference on Information Fusion, FUSION 2016, Heidelberg, Germany, July 5-8, 2016.



2015


[8] H.Y.Zhu, C.Wang, Joint track-to-track association and sensor registration at the track level, Digital Signal Processing, 2015, 41: 48–59.

[9] H.Y.Zhu, K.Guo, DOA estimation based on the microphone array for the time-varying number of sound signals, Proc. of 18th International Conf. on Information Fusion, Washingtong DC,US, 2015.

[10] H.Y.Zhu, P.D.Zhang, T.T.Ma. Research on measurement set partitioning method for tracking multiple extended targets, Proc. of the 27th Chinese Control and Decision Conf., QingDao, China, 2015.


2014


[11] H.Y.Zhu, Q.Z.Zhai, C.Z.Han, M.W.Yu, Estimation fusion algorithms in the presence of partially known cross-correlation of local estimation errors, Information Fusion, 2014, 18: 187- 196.

[12] H.Y.Zhu, S.Chen, Track fusion in the presence of sensor biases, IET Signal Processing, 2014, 8(9): 958-967.

[13] H.Y.Zhu, S.Chen, C.Z.Han, Fusion of Gaussian mixture models for possible mismatches of sensor model, Information Fusion, 2014, 20: 203-212.

[14] H.Y.Zhu, S.Y.Han, Track-to-track association based on structural similarity in the presence of sensor biases, Journal of Applied Mathematics, Special issue: Mathematical Modeling and Optimization of Industrial Problems, 2014, 1:1-8.

[15] H.Y.Zhu, C.Wang, Integrated data association and bias estimation in the presence of missed detections, Proc. of 17th International Conf. on Information Fusion, Salamanca, Spain, 2014.

[16] H.Y.Zhu, T.T.Ma, A Random matrix-based method for tracking multiple extended targets, Proc. of 17th International Conf. on Information Fusion, Salamanca, Spain, 2014.


2013-2004


[17] H.Y.Zhu and Q.Z.Zhai, A global optimal Gaussian mixture reduction approach based on component merging, Chinese Journal of Electronics, 2013, 22(4): 763-768.

[18] H.Y.Zhu,S.Chen, Fusion of possible biased local estimates in sensor network based on sensor selection, Proc. of 16th International Conf. on Information Fusion, Istanbul, Turkey, 2013.

[19] Y.L.Han, H.Y.Zhu, C.Z.Han, A Gaussian-mixture PHD filter based on random hypersurface model for multiple extended targets, Proc. of 16th International Conf. on Information Fusion, Istanbul, Turkey, 2013.

[20] H.Y.Zhu, C.Z.Han. A Reduced Gaussian Mixture Representation Based On Sparse Modeling. Proceedings of the 15th International Conference on Information Fusion, Singapore2012.

[21] Hongyan zhu and chongzhao han. Particle labeling PHD filter for multitarget track-valued estimates. Proceedings of the 14th International Conference on Information Fusion, Chicago2011.

[22] Hongyan zhu and chongzhao han. An extended target tracking method  based  on random finite set measurements. Proceedings of the 14th International Conference on Information Fusion, Chicago2011.

[23] Xiaoxi Yan, Chongzhao Han, Hongyan Zhu. Component Pruning Based on Entropy Distribution in Gaussian Mixture PHD Filter. Proceedings of the 14th International Conference on Information Fusion, Chicago2011.

[24] Weifeng Liu, chongzhao han, LeiMing and HongYan Zhu. Multitarget States Extraction for Probability Hypotheses Density Using Finite Mixture Models. IEEE Trans on AES, May 2010.

[25] H.Y.Zhu, C.Z.Han. Graphical models-based track association algorithm. Proceedings of the 10th International Conference on Information Fusion, Chicago2008.

[26] Hongyan zhu, chongzhao han and chen li. Graphical model-based track association algorithm. Proceedings of the 10th International Conference on Information Fusion, Canada 2007.

[27] Li C, Wang H, Han CZ and Zhu HY. Data association for target tracking by several passive sensors.2007  IEEE International Conference on Systems, Man and Cybernetics (SMC), Canada, Oct. 2007.

[28] Li C, Han CZ, Chen HM and Zhu HY. Data association for target tracking by IR sensors. Aircraft Engineering and Aerospace technology, 2007, 79(5): 511-517.

[29] Zhansheng Duan, X.Rong Li, Chongzhao Han, Hongyan Zhu. Sequentia Unscented Kalman Filter for Radar Target Tracking with Range Rate Measurements. Proceedings of the 8th Internatinal Conference on Information Fusion. Philadephia, USA, 2005.

[30] Hongyan Zhu, Chongzhao Han and Hong Han. A Fast Approach for Track Initiation and Termination. Chinese Journal of Electronics 13 (2): 325-3282004.


 

联系方式

联系电话:029-82663948-809

Email:hyzhu@mail.xjtu.edu.cn

联系地址:西安交通大学电子与信息工程学院 邮政编码:710049