6B.5
Adaptive Waveform Design Applications for a Multi-Sector MPAR

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Tuesday, 6 January 2015: 2:30 PM
132AB (Phoenix Convention Center - West and North Buildings)
James M. Kurdzo, University of Oklahoma, Norman, OK; and R. Palmer, B. L. Cheong, R. Kelley, and C. Fulton

The future of the MPAR program is dependent on numerous research thrusts that assume the use of individual transmit/receive elements in order to achieve a multi-function phased array architecture. In order to alleviate excessive heat dissipation and cost concerns, it will be critical to utilize low-power solid-state transmit elements and pulse compression techniques to achieve the necessary sensitivity and range resolution. Recent advances in frequency-modulated pulse compression techniques have afforded the ability to maximize sensitivity and sidelobe performance within a given time-bandwidth specification; however, waveform design has the potential to bring numerous other spectrum-based advancements to the MPAR mission. Though a flexible, multi-sector array provides opportunities to operate groups of these sectors independently and simultaneously, concerns regarding spectral management and interference between sectors (and other networked systems) are significant. This is true for both multi-faced planar and cylindrical array configurations. Exploitation of the available spectrum and the flexibility between different apertures could yield advantages in spatial and temporal resolution, data quality, radio frequency interference mitigation, and other problems that commonly affect weather radar systems. A generalization of recent waveform design techniques into a multi-aperture waveform "family" is presented. Simulations of a four-aperture waveform family with both long and fill pulses in time-frequency multiplexed pairs are carried out and optimized for minimal interference. The ability to re-distribute base waveform families for dynamic application in a cognitive sense is discussed, and examples of spectrum sharing between apertures for increased data quality and temporal resolution are presented.