研究领域:

智能信息处理、深度学习、多源信息融合、机器视觉、目标检测、定位、跟踪与识别。

  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、以及企业横向委托项目。 

著作

 （1）韩崇昭,朱洪艳 , 段战胜.《多源信息融合》（第二版），清华大学出版社,2010.

 （2）杨清宇，马训明，朱洪艳，连峰. 《现代控制理论》（第二版），西安交通大学出版社，2020.

论文

2020

[1]Wenyan Zhu, Hongyan Zhu. Multi-signal detection and parameter estimation fusion with an improved utility function. Digital Signal Processing 98 (2020) 102641, pp 1-11.

[2] Yao Guo, Hongyan Zhu, Xudong Dang. Tracking multiple acoustic sources by adaptive fusion of TDOAs across microphone pairs. Digital Signal Processing 106 (2020) 102853, pp1-13.

[3] Xudong Dang, Hongyan Zhu. A feature-based data association method for multiple acoustic source localization in a distributed microphone array. The Journal of the Acoustical Society of America, accepted.

2019

[1] Xudong Dang , Qi Cheng and Hongyan Zhu. Indoor Multiple Sound Source Localization via Multi-Dimensional Assignment Data Association. IEEE/ACM transactions on Audio, Speech and Language Processing, 27(2), pp. 1944-1956, Dec. 2019.

[2]Wen Ma, Hongyan Zhu. Multi-Sensor Passive Localization Based on Sensor selection. Proceedings of 2019 International Conference on Information Fusion, Ottawa, Canada, July 2-5, 2019.

     2018

[1] H.Y. Zhu, W.Y. Zhu, "Distributed Detection and Estimation Fusion by Maximizing Expected Utility," 2018 21st International Conference on Information Fusion (FUSION), Cambridge, United Kingdom, 2018, pp. 1955-1960.

[2] H.Y. Zhu，X.D. Dang, Z..L. Li and Q.B. Ge, "Sound Source Localization Based on Robust Least Squares in Reverberant Environments," 2018 21st International Conference on Information Fusion (FUSION), Cambridge, United Kingdom, 2018, pp. 2029-2035.

[3] X.D.Dang, H.Y. Zhu and Q. Cheng, "Multiple Sound Source Localization Based on a Multi-Dimensional Assignment Model," 2018 21st International Conference on Information Fusion (FUSION), Cambridge, United Kingdom, 2018, pp. 1732-1737.

     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, Singapore，2012.

[21] Hongyan zhu and chongzhao han. Particle labeling PHD filter for multitarget track-valued estimates. Proceedings of the 14th International Conference on Information Fusion, Chicago，2011.

[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, Chicago，2011.

[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, Chicago，2011.

[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, Chicago，2008.

[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): 325-328，2004.

 ​​​​​​​

1、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；

2、“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）；

3、“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）。