ITTC Project

Multidimensional Signal Processing for Sensing & Communications

Project Award Date: 06-01-2012


Leveraging the notion of STAP used for clutter cancellation in airborne/space-based radar, the multiplicative increase in degrees of freedom afforded by multidimensional coupling can be expanded to include other dimensions as well. Performing this coupling on transmit also has the potential to improve receive detection/estimation performance via the resulting increased diversity of the transmit signal. This effort will address how to mathematically model and optimize physical multidimensional emissions through the use of analytical structures for physical waveform implementation. Likewise, appropriate structures for clutter cancellation will be investigated where, because these waveform-diverse schemes couple the waveform dimension to angle and/or Doppler, the traditional approach of STAP to use the range domain as training data is no longer available. Rank reduction transformation approaches will be explored as a means to obtain training data for adaptive processing. Another component of this effort will address the waveform-diverse embedding of LPI communications into clutter. Building upon recent advances in LPI symbol detection, a soft-decision detector for symbol estimation will be investigated that may have broader implications for error correction coding and decoding.
Obtaining physical emission structures and enabling effective clutter cancellation for these waveform-diverse sensing schemes will facilitate their transition into actual fielded systems. It is expected that the deployment of these waveform-diverse radar and communication systems will be an enabling technology for Air Force goals of total spectral dominance.


Faculty Investigator(s): Shannon Blunt (PI)

Student Investigator(s): Justin Metcalf, John Jakabosky, Patrick McCormick, Dakota Henke, Brian Cordill

Project Sponsors

Primary Sponsor(s): Air Force Office of Scientific Research

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