Skip to main content

Phase II STTR: Signal Fragmentation Based on Sampling with Wavelets (Wavelet-Based Adaptive Antenna Systems)

PI: Dr. Semyon Tsynkov (Professor of Mathematics and Associate Director, CRSC)

Support: US Army – Army Research Office (ARO)/Albanese Defense and Energy Development Company LLC (ADED LLC)

Period of Performance: December 1st, 2019 — November 30th, 2021

Budget: $1,025,000 (NCSU share $300,000)

Summary: We propose an innovative mathematical approach to the analysis and design of multi-function adaptive antenna sys-tems. It uses the idea of signal fragmentation that has passed significant prior testing and employs the methods and results from sampling theory, approximation theory, and numerical optimization. The fragmentation of a signal into a combination of short elementary pulses (wavelets) allows the radiation of long waves by small size antennas/arrays, which would otherwise be inefficient. This, in turn, enables performing various diverse tasks, e.g., radar imaging and telecommunications, by one and the same compact antenna system. During Phase I, we considered CW signals. Our key goal is to optimize the energy performance of the array while maintaining the desired spectral “purity” of the composite signal and satisfying some additional constraints on its shape (related, e.g., to bounds on the input current rise times). Phase II will include multi-frequency signals (AM, FM, FMCW, chirped pulses, frequency-shift keying (FSK), and Baker codes (e.g., direct-sequence spread spectrum (DSSS) modulation), non-isotropic antennas (analysis and fabrication), more comprehensive optimization, and development of a well-documented “sharable” software package.