Advanced Wireless Integration with Infrastructure Systems

To design and deploy adaptive multimodal sensor electronics and wireless sensor network (WSN) for smart infrastructure monitoring and management. The research will focus on the following aspects: (1) designing adaptive multimodal sensor node that can host different sensors and can dynamically control sensor operating parameters in response to varying sensing conditions; (2) exploring in-sensor-node computing technology including digital approximating computing and analog computing to leverage sensor intelligence and reduce power consumption; (3) investigating AI for sensor data processing and feature extraction.

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Cognitive Ground Penetrating Radar for Subsurface Sensing and Mapping

Determining what lies beneath the ground surface without digging is a ubiquitous problem that motivates the development of sensory instruments with intelligence, sensitivity, and situationally aware information processing capabilities and control. The research explores beyond modern geophysical instruments that produce useful but fuzzy results requiring intensive expertise for data interpretation and tedious grid-based experimental surveys, to free-moving autonomous intelligent systems that operate in data-driven adaptive manners being able to produce high quality and fidelity subsurface tomographic images. The key research idea is to design a new ground penetrating radar (GPR) as a cognitive sensor based on cyber-physical system principles. Realizing this require researching building and testing systems with increasing capability and complexity beginning with individual GPRs, followed by swarms of cognitive GPRs. The research involves collective efforts on novel high-performance radar circuit design, radar signal processing, machine learning and augmented reality (AR) for real time sensing and 3D visualization.

UWB Health Care Radar for Non-Invasive Human Vital Signs Detection and Posture Imaging

In this research, we explore ultra-wide band (UWB) radar technology to develop an innovative non-invasive detection system that can remotely capture human vital signs, specifically respiratory movement and heartbeat signals, and monitor body postures and movement for health care applications. The radar makes use of the Doppler-effect and the micro-Doppler effect to monitor and capture dynamic vital signs, and synthetic aperture radar (SAR) technologies to form posture images. In the sensing, the radar emits a series of narrow electromagnetic (EM) pulse beams. The reflected wave from the human subject will be modulated by the subject's body movements, e.g., the respiration the heartbeat, torso, legs, etc. The modulation signal's frequency variation is proportional to the relative velocity of body movement to the radar transceiver. By characterizing the frequency variation, the vital signs can be detected and characterized. The development of this health care radar system consists of the following major elements: 1). UWB radar circuit that generates, amplifies, receives, and filters various MW/RF signal components; 2). Small size antennas of high fidelity and sensitivity; 3). Signal processing method for low amplitude non-stationary human vital signs extraction and interference noise elimination. 4) SAR image formation and characterization.

Joint Radar and Communication Systems

Sharing the frequency spectrums between radar and communication systems has aroused tremendous attentions as it can significantly leverage efficiencies of limited spectral resources. Further, combining radar and communication systems to co-use the hardware platform as well as the frequency band can benefit both sensing and signaling operations to achieve many more novel applications. In this research, we investigate software defined radio/radar (SDRR) by exploring adaptive multiband RF and digital circuit design and waveform design and optimization.