Reconfigurable metasurfaces (RMSs) are promising solutions for beamforming and sensing applications including 5G and beyond wireless communications, satellite and radar systems, and biomarker sensing. In this work, three distinct RMS architectures – reconfigurable intelligent surfaces (RISs), meta-transmission lines (meta-TLs), and substrate integrated waveguide leaky-wave antennas (SIW-LWAs) are developed and characterized. The ever-increasing demand for higher data rates and lower latencies has propelled the telecommunications industry to adopt higher frequencies for 5G and beyond wireless communications. However, this transition to higher frequencies introduces challenges in terms of signal coverage and path loss. Many base stations would be necessary to ensure signal fidelity in such a setting, making bulky phased array-based solutions impractical. Consequently, to meet the unique needs of 5G and beyond wireless communication networks, this work proposes the use of RISs characterized by low-profile, low-RF losses, low-power consumption, and high-gain capabilities, making them excellent candidates for future wireless communication applications. Specifically, RISs at sub-6GHz, mmWave and sub-THz frequencies are analyzed to demonstrate their ability to improve signal strength and coverage. Further, a linear meta-TL wave space is designed to achieve miniaturization of true-time delay beamforming structures such as Rotman lenses which are traditionally bulky. To address this challenge, a modified lumped element TL model is proposed. A meta-TL is created by including the mutual coupling effects and can be used to slow down the electromagnetic signal and realize miniaturized lenses. A proof-of-concept 1D meta-TL is developed to demonstrate about 90% size reduction and 40% bandwidth improvement. Furthermore, a conformable antenna design for radio frequency-based tracking of hand gestures is also detailed. SIW-LWA is employed as the radiating element to couple RF signals into the human hand. The antenna is envisaged to be integrated in a wristband topology and capture the changes in the electric field caused by various movements of the hand. The scattering parameters are used to track the changes in the wrist anatomy. Sensor characterization showed significant sensitivity suppression due to lossy multi-dielectric nature tissues in the wrist. However, the sensor demonstrates good coupling of electromagnetic energy making it suitable for on-body wireless communications and magnetic resonance imaging applications.

The micromotions (e.g. vibration, rotation, etc.,) of a target induce time-varying frequency modulations on the reflected signal, called the micro-Doppler modulations. Micro-Doppler modulations are target specific and may contain information needed to detect and characterize the target. Thus, unlike conventional Doppler radars, Fourier transform cannot be used for the analysis of these time dependent frequency modulations. While Doppler radars can detect the presence of a target and deduce if it is approaching or receding from the radar location, they cannot identify the target. Meaning, for a Doppler radar, a small commercial aircraft and a fighter plane when gliding at the same velocity exhibit similar radar signature. However, using a micro-Doppler radar, the time dependent frequency variations caused by the vibrational and rotational micromotions of the two aircrafts can be captured and analyzed to discern between them. Similarly, micro-Doppler signature can be used to distinguish a multicopter from a bird, a quadcopter from a hexacopter or a octacopter, a bus from a car or a truck and even one person from another. In all these scenarios, joint time-frequency transforms must be employed for the analysis of micro-Doppler variations, in order to extract the targets’ features.

Due to ample bandwidth, THz radiation provides richer radar signals than the microwave systems. Thus, a Terahertz (THz) micro-Doppler radar is developed in this work for the detection and characterization of the micro-Doppler signatures of quadcopters. The radar is implemented as a continuous-wave (CW) radar in monostatic configuration and operates at a low-THz frequency of 270 GHz. A linear time-frequency transform, the short-time Fourier transform (STFT) is used for the analysis the micro-Doppler signature. The designed radar has been built and measurements are carried out using a quadcopter to detect the micro-Doppler modulations caused by the rotation of its propellers. The spectrograms are obtained for a quadcopter hovering in front of the radar and analysis methods are developed for characterizing the frequency variations caused by the rotational and vibrational micromotions of the quadcopter. The proposed method can be effective for distinguishing the quadcopters from other flying targets like birds which lack the rotational micromotions.