AESA-based RADAR Performance in Complex Sensor Environments

Many current United States Navy (USN) OPSIT/TACSIT scenarios comprise demanding dynamic environments for airborne sensors. The ability to task or mode interleave with adaptive scheduling is essential to achieving desired sensor/mission effectiveness. Both active electronically scanned array (AESA) and conventional mechanically scanned antenna (MSA) airborne multi-mode radar systems will require energy timeline resource management to realize their full performance capabilities. Furthermore, the programmable nature of many modern AESA based sensor architectures allows real-time modification of antenna pattern and waveform characteristics. Real-time adaptive optimization of AESA control and scheduling over the implicitly large number of degrees of freedom is computationally impractical without sufficient constraints. In contrast, non-adaptive legacy resource management approaches rely exclusively on rule-based constrained methodologies that relax computational concerns, but significantly under utilize radar energy timeline resources. Recent real-time computer systems research in optimum scheduling in complex dynamic environments has produced computationally efficient approximate solutions that are attractive for use with rule-based constraints. LSI proposes to develop and evaluate hybrid rule-based constrained optimization techniques for real-time adaptive optimization of airborne AESA and MSA control and scheduling. These techniques will apply to airborne AESA and MSA radar systems of interest to the USN and address both air-to-air and air-to-ground operation.