Selected Research Projects

  • MIMO Radars Using Sparse Sensing: MIMO radars require huge amount of data and very high sampling rate, which are costly for sensing, collecting, and processing. This project proposes novel approaches based on sparse sensing for substantially reducing the amount of data, while ensuring radar performance. The models and algorithms have great potential for big data and massive MIMO applications.

  • MIMO Radars and Communication Spectrum Sharing: The exponentially increasing RF bandwidth demand and the spectrum resources scarcity raise an urgent need to improve the spectrum efficiency. Recently, the commercial wireless communication systems are allowed to access spectrum allocated to radar. It is challenging to accommodate the co-existence of two heterogenous systems, especially radars are usually used for public security purposes. This project proposes several frameworks to address the challenges by exploiting MIMO and OFDM techniques.

  • Microphone Array Signal Processing for Speech and Traffic Audio Applications:

    • Implemented a realtime microphone array demo system with features including speech enhancement, speaker localization and automatic camera steering towards the active speaker.

    • Prototyped a 32-channel microphone array (traffic) audio acquisition and processing platform for traffic audio feature extraction and traffic incident detection; implemented Delay&Sum and MVDR beamforming for traffic audio preprocessing, achieving 10-15dB interference suppression.