Research Profile
Research Experience
Radar Signal Processing and Intelligent Sensing
Research on radar signal processing, intelligent sensing, image enhancement, and 3D reconstruction under low-SNR and complex observation conditions.
- Signal Processing: Developed signal processing methods for non-stationary and low-SNR radar observations.
- Detection & Estimation: Developed weak-target detection and nonlinear parameter estimation methods for robust motion estimation and high-precision imaging.
- Self-Supervised Enhancement: Developed self-supervised methods for radar signal and image denoising without requiring clean reference data.
- Learning-Based Perception: Investigated Transformer-based methods for learning representations from radar observations.
- 3D Sensing: Developed multi-view reconstruction methods for sparse and noisy observations.
UAV-Based Radar Sensing and 3D Reconstruction
Developed UAV-based radar sensing, signal processing, image enhancement, and 3D reconstruction methods for complex real-world environments.
- Data Acquisition: Conducted 40+ UAV sorties at 170–260 m for real-world radar sensing and data collection.
- Signal & Image Processing: Developed physics-based motion estimation and self-supervised denoising methods for low-SNR and complex-motion observations, improving SNR by 10–15 dB.
- 3D Reconstruction: Developed multi-view reconstruction methods using ADMM-Net and 3DGS, achieving sub-meter reconstruction accuracy for representative urban scenes.
- Real-World Validation: Conducted 100+ experiments using TB-scale real sensor data collected in complex environments.
mmWave Radar-Based Human Activity Recognition
Developed mmWave radar-based human gesture recognition methods covering sensor data acquisition, signal processing, feature extraction, and learning-based classification.
- Data Acquisition: Built an AWR1642 mmWave radar sensing system and collected data from 10 gesture classes.
- Signal Processing: Applied filtering and CFAR detection to extract range, velocity, and angle features.
- Feature Learning: Developed a dual-branch network to fuse complementary radar features for dynamic gesture classification.
- Results: Achieved >94.5% recognition accuracy through data augmentation and model optimization.
Intelligent Radar Perception of Celestial Targets
Developed radar observation modelling, target parameter estimation, sparse imaging, and intelligent perception methods for challenging low-SNR and sparse-observation scenarios.
- Observation Modelling: Investigated multi-dimensional sensing mechanisms using multi-frequency, multi-polarization, and multi-station observations.
- Target Estimation: Developed high-precision parameter estimation and imaging methods using physical priors and sparse observations.
- Learning-Based Imaging: Combined sparse reconstruction with deep learning to improve reconstruction quality under challenging observation conditions.
- Experimental Validation: Participated in extensive real-world sensor experiments, covering data acquisition, algorithm validation, and empirical analysis.
Selected Publications & Patents
A Parametric 3-D ISAR Imaging Method of Celestial Target Under Low SNR
IEEE Transactions on Geoscience and Remote Sensing | Co-author
Published
Multi-Dimensional Spread Target Detection with Across Range-Doppler Unit Phenomenon Based on Generalized Radon-Fourier Transform
Remote Sensing | First Author
Published
Scattering-Aware Multi-View Masked Networks for Self-Supervised Radar Denoising
IEEE Transactions on Geoscience and Remote Sensing | First Author
Under Review
A Self-Supervised Radar Sparse Imaging Method via Physics-Aware Imputation Network
IEEE Transactions on Aerospace and Electronic Systems | First Author
Under Review
An Adaptive 3-D Reconstruction Method for Targets Based on Multi-View Self-Supervised Framework under Low SNR
First Author
Under Review
Method for Multi-View 3D Reconstruction under Low SNR
Chinese Invention Patent | First Student Inventor
Granted
Image Denoising Method Based on Multi-Angle Observations and Self-Supervised Learning
Chinese Invention Patent | First Student Inventor
Granted
Self-Supervised Image Denoising Method Based on an Adaptive Masking Strategy
Chinese Invention Patent | First Student Inventor
Patent Application
Image Reconstruction Method Based on a Self-Supervised Inpainting Network
Chinese Invention Patent | First Student Inventor
Patent ApplicationEducation
Relevant Coursework: Signals and Systems, Digital Signal Processing, Communication Principles.
Technical Skills
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Radar Signal Processing
- Target detection and parameter estimation
- CFAR detection
- Time-frequency analysis
- SAR / ISAR imaging
- Low-SNR signal enhancement
-
Sensing Systems
- mmWave radar
- UAV-based sensing
- Multi-view sensing
- Real-world sensor data acquisition
-
Deep Learning
- Self-supervised learning
- Transformer
- Diffusion models
- CNN-based feature learning
-
Image Processing
- Image enhancement and denoising
- Sparse image reconstruction
- Structure-preserving reconstruction
-
3D Reconstruction
- Multi-view reconstruction
- Sparse-view reconstruction
- NeRF
- 3D Gaussian Splatting (3DGS)
- ADMM-based deep unfolding
-
Programming
- Python / PyTorch
- MATLAB
- C / C++
-
Software & Hardware
- CST Studio / FEKO
- MeshLab / COLMAP
- STK
- mmWave radar / LiDAR
- Anechoic chamber experiments
Honors & Awards
China Scholarship Council Scholarship
Funded joint PhD research at the University of Auckland.
Beijing Outstanding Graduate
Recognized for outstanding academic achievement and comprehensive performance.
First-Class Scholarships (26 Awards)
Received multiple municipal- and university-level scholarships for academic excellence.
National Level-II Athlete Standard in Marathon Running
Long-term endurance athlete with 20+ marathon and road-race finishes.
AHA / Red Cross First Aid Instructor
Certified first aid instructor with experience supporting large-scale events.
Outstanding Student Leader (3 Awards)
Recognized three times for leadership, teamwork, and contributions to student activities.
Leadership & Activities
Summer Teaching Volunteer Program, China
- Initiated and organized educational outreach programs in rural areas, coordinating volunteer recruitment, curriculum design, school engagement, and team management.
American Heart Association & Beijing Red Cross
- Delivered CPR and first-aid training to more than 1,000 participants across universities, companies, and public events.
