[1] 国家自然科学基金，基于L1范数正则化的大场景实时稀疏SAR成像方法研究，2020/01-2022/12，在研，主持

[2] 江苏省自然科学基金，星载和机载SAR稀疏无模糊快速成像方法研究，2019/07-2022/06，在研，主持

[3] 江苏省科协青年科技人才托举工程，2019/07-2021/06，在研，主持

[4] 南京航空航天大学科研启动基金，基于稀疏信号处理的合成孔径雷达成像技术研究，2018/12-2020/11，在研，主持

[5] 工信部民机专项，机载极化气象雷达信号处理技术研究，2018/12-2020/11，在研，子课题负责人

[6] 雷达成像与微波光子技术教育部重点实验室基金，基于多孔径捷变技术的新体制HRWS-SAR信号处理方法，2019/07-2021/06，在研，参与

[7] 国家自然科学基金面上项目，基于结构稀疏的宽角SAR成像研究，2016/01-2019/12，在研，参与

[8] 国家基础研究计划（973计划），稀疏微波成像的理论，体制和方法研究， 2010/01-2014/01，结题，参与

[9] 中国科学院/国家外专局重点项目创新团队国际合作伙伴计划，先进微波探测与信息处理，2013/01-2017/01，结题，参与

[10] 863计划，***海洋***感知***，2015/09-2016/07，结题，参与

(一) 期刊论文

[1] Hui Bi, Jingjing Wang, and Guoan Bi. Wavenumber domain algorithm based FMCW SAR sparse imaging. IEEE Transactions on Geoscience and Remote Sensing. 2019, 57(10): 7466-7475. （SCI）

[2] Hui Bi, Guoan Bi, Bingchen Zhang, and Wen Hong. Complex image based sparse SAR imaging and its equivalence. IEEE Transactions on Geoscience and Remote Sensing. 2018, 56(8): 5006-5014. （SCI）

[3] Hui Bi, Bingchen Zhang, XiaoXiang Zhu, Chenglong Jiang, and Wen Hong. Extended chirp scaling-baseband azimuth scaling based azimuth-range decouple L1 regularization for TOPS SAR imaging via CAMP. IEEE Transactions on Geoscience and Remote Sensing. 2017, 55(7): 3748-3763. （SCI）

[4] Hui Bi, Bingchen Zhang, XiaoXiang Zhu, Wen Hong, Jinping Sun, and Yirong Wu. L1 regularization based SAR imaging and CFAR detection via complex approximated message passing. IEEE Transactions on Geoscience and Remote Sensing. 2017, 55(6): 3426-3440. （SCI）

[5] Hui Bi,Guoan Bi, Bingchen Zhang, Wen Hong, and Yirong Wu. From theory to application: Real-time sparse SAR imaging. IEEE Transactions on Geoscience and Remote Sensing. 2019. (In Press) （SCI）

[6] Hui Bi, Wen Hong, Bingchen Zhang, Jinping Sun, Jingjing Wang, and Guoan Bi. An improved iterative thresholding algorithm for sparse SAR imaging. IEEE Transactions on Geoscience and Remote Sensing. 2019. (In Press) （SCI）

[7] Hui Bi, Jingjing Zhang, and Guoan Bi. Airborne FMCW SAR sparse data processing via frequency scaling algorithm. IEEE Geoscience and Remote Sensing Letters. 2019. (Under Review) （SCI）

[8] Hui Bi, Guoan Bi, and Daiyin Zhu. The wavenumber domain algorithm for high-squint FMCW SAR imaging. Science China Information Sciences. 2019. (Under Review) （SCI）

[9] Hui Bi and Guoan Bi. A novel iterative soft thresholding algorithm for L1 regularization based SAR image enhancement. Science China: Information Sciences. 2019, 62(4): 049303: 1-3. （SCI）

[10] Hui Bi, Jianguo Liu, Bingchen Zhang, and Wen Hong. Baseline distribution optimization and missing data completion in wavelet-based CS-TomoSAR. Science China: Information Sciences. 2018, 61(4): 042302:1-9. （SCI）

[11] Hui Bi, Bingchen Zhang, XiaoXiang Zhu, and Wen Hong. Azimuth-range decouple based L1 regularization method for wide ScanSAR imaging via extended chirp scaling. Journal of Applied Remote Sensing. 2017, 11(1): 015007:1-12. （SCI）

[12] Hui Bi, Bingchen Zhang, Zhengdao Wang, and Wen Hong. Lq regularization-based synthetic aperture radar image feature enhancement via iterative thresholding algorithm. Electronics Letters. 2016, 52(15): 1336-1338. （SCI）

[13] Hui Bi, Bingchen Zhang, and Wen Hong. Lq regularization-based unobserved baselines' data estimation method for tomographic SAR inversion. Journal of Applied Remote Sensing. 2016, 10(3): 035014:1-10. （SCI）

[14] Hui Bi, Bingchen Zhang, Wen Hong, and Shengli Zhou. Matrix completion based airborne tomographic SAR inversion under missing data. IEEE Geoscience and Remote Sensing Letters. 2015, 12(10): 2346-2350. （SCI）

[15] Hui Bi, Chenglong Jiang, Bingchen Zhang, Zhengdao Wang, and Wen Hong. Radar change imaging with undersampled data based on matrix completion and Bayesian compressive sensing. IEEE Geoscience and Remote Sensing Letters. 2015, 12(7): 1546-1550. （SCI）

[16] Hui Bi, Bingchen Zhang, and Wen Hong. Matrix completion-based distributed compressive sensing for polarimetric SAR tomography. Science China: Information Sciences. 2015, 58(10): 119301:1-3. （SCI）

[17] 毕辉, 张冰尘, 洪文. 基于RIPless理论的层析SAR成像航迹分布优化方法. 航空学报. 2016, 37(2): 680-687. （EI）

[18] 毕辉, 蒋成龙，王万影，张冰尘, 洪文. 层析合成孔径雷达成像航迹分布优化方法. 系统工程与电子技术. 2015, 37(7): 1788-1792.（EI）

（二）会议特邀报告

[19] Hui Bi. Sparse SAR imaging: From theory to practical application. Outstanding Doctoral Forum and Young Scientists Forum, 10th International Conference on Image and Graphics, Beijing, China, Aug. 23-25, 2019.

[20] Hui Bi. Real-time data processing in sparse SAR imaging. 11th IEEE International Conference on Advanced Infocomm Technology, Jinan, China, Oct. 18-20, 2019.

(三) 会议论文

[21] Hui Bi, Guoan Bi, Bingchen Zhang, and Wen Hong. Real-time data processing in sparse SAR imaging. 11th IEEE International Conference on Advanced Infocomm Technology, pp. 1-5, Jinan, China, Oct. 18-20, 2019.

[22] Hui Bi and Guoan Bi. Performance analysis of iterative soft thresholding algorithm for L1 regularization based sparse SAR imaging. IEEE Radar Conference: Revolutions in Radar, pp. 1-6, Boston, USA, April 22-26, 2019.

[23] Hui Bi, Guoan Bi, Lu Wang, Xiumei Li, and Xianpeng Wang. Airborne FMCW SAR sparse imaging: Initial results. The 23rd International Conference on Digital Signal Processing (DSP), pp: 1-5, Shanghai, China, November 19-21, 2018.

[24] Hui Bi, Guoan Bi, Bngchen Zhang, and Wen Hong. A novel iterative thresholding algorithm for complex image based sparse SAR imaging. 12th European Conference on Synthetic Aperture Radar (EUSAR), pp: 1-5, Aachen, Germany, June 4-7, 2018.

[25] Hui Bi, Bingchen Zhang, XiaoXiang Zhu, and Wen Hong. Lq regularization method for spaceborne SCANSAR and TOPS SAR imaging. 11th European Conference on Synthetic Aperture Radar (EUSAR), pp: 1-4, Hamburg, Germany, June 6-9, 2016.

[26] Hui Bi, Bingchen Zhang, XiaoXiang Zhu, Wen Hong, and Yirong Wu. CFAR detection for the complex approximated message passing reconstructed SAR image. 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), pp: 133-137, Aachen, Germany, September 19-22, 2016.

(四) 编写专著

[27] 参与编写中文专著《稀疏微波成像导论》

[28] 参与编写中文专著《稀疏微波成像应用》