The NSF funded research project on “Digital Hardware Architectures for RF Multi-Dimensional Arrays (DHARMA)” with PIs Arjuna Madanayake and Xin Wang (SUNY, Stony Brook) is underway. The PIs thank Program Officer Dr George Haddad (NSF-CCSS) for supporting this research.
Award Abstract #1408361 Title: Collaborative Research: Electronically-Scanned Wideband Digital Aperture Antenna Arrays using Multi-Dimensional Space-Time Circuit-Network Resonance: Theory and Hardware.
An aperture array is a group of antennas that can be deployed in particular geometric patterns to detect radio signals at a given range of frequencies. Using an array is beneficial for electrical engineering because it can magnify a radio signal in the direction of that signal while suppressing noise and interference through a process known as beamforming. In addition, an antenna array can be used to detect the direction and distance of the signal’s source. Aperture arrays are a crucial component of scientific instruments that measure the spatial distribution of radio sources. For example, radio telescopes, such as the Square Kilometer Array (SKA) instrument, rely on aperture arrays to generate precise radio images of electromagnetic sources for experimental cosmology and space science. These instruments image the sky using closely spaced radio beams known as radio pixels. Closely packed sets of such beams can be achieved by using hexagonal pixel grids, which are considered ideal for scientific studies. In order to build aperture beamformers to be used for a specific purpose, efficient schemes for processing the antenna array signals must be developed to reduce the computing time, energy consumption, and costs for the hardware required in the system. The proposed research creates new algorithms and digital computing architectures that will produce highly-focused hexagonal radio pixels for the most demanding of microwave imaging applications. The same aperture arrays are used in radar and wireless communication systems for signature detection and signal intelligence. In fact, aperture arrays are absolutely essential for national security and public safety from a threat detection perspective. In addition to its scientific merits and benefits for national security, this project will train highly qualified personnel (HQP), who will contribute to commercial industry, scientific research, public safety agencies, and the defense sector. Specific efforts will focus on promoting Women in Engineering programs in higher education to recruit and guide female engineering students at both the graduate and undergraduate levels.
The proposed research tackles the problem of highly directional sparse aperture arrays using the mathematical properties of multi-dimensional recursive digital filters. The NSF-sponsored effort will develop hardware systems for aperture arrays based on the proposed concept of network-resonant phased-arrays (NRPAs). Multi-dimensional (MD) circuit theory and digital hardware form an enabling technology for imaging algorithms that can greatly improve performance over traditional technologies. This research proposes groundbreaking techniques based on array signal processing, circuits and systems. It will result in a significant improvement in the directional sensitivity while using a lower number of array elements compared to traditional phased array receivers of the same sensitivity. The proposed NRPAs combine the concept of network resonance with phased array technology to gain significant improvement in both directionality and sensitivity. The MD circuit theoretical concept of network resonance allows digital beamformers to have complex pole manifolds. These properties are shown to have advantages in terms of ultra-wideband frequency response, exceptional directionality, multi-beams with shape control, rapid steerability, and low computational complexity. This project investigates radio beams with a hexagonal sky-print for optimal sensing and microwave imaging over wide fields-of-view and bandwidths. The proposed NRPAs will be extended to both sparse and random arrays via theoretical formulations for decreasing hardware cost, reducing energy expended in computers and increasing design flexibility.
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