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Given the increasing utilization and dependence on ISR information, operators and imagery analysts monitoring
intelligence feeds seek a capability to reduce processing overload in transformation of ISR data to actionable
information. The objective they seek is improvement in time critical targeting (TCT) and response time for mission
events. Existing techniques addressing this problem are inflexible and lack a dynamic environment for adaptation to
changing mission events. This paper presents a novel approach to ISR information collection, processing, and response,
called the ISR Context Switching System (ISR-CSS). ISR-CSS enables ground, sea, and airborne sensors to perform
preliminary analysis and processing of data automatically at the platform before transferring actionable information back
to ground-base operators and intelligence analysts. The on-platform processing includes a catalogue of filtering
algorithms concatenated with associated compression algorithms that are automatically selected based on dynamic
mission events. The filtering algorithms employ tunable parameters and sensitivities based on the original mission plan
along with associated Essential Elements of Information (EEI), data type, and analyst/user preferences. As a mission
progresses, ISR-CSS incorporates adaptive parameter updates (model-based, statistics-based, learning-based, and event-driven),
providing increased tactical relevant data. If a mission transforms dramatically, where unexpected manual
guidance is required, then ISR-CSS allows tactical end-user direct-to-sensor tasking. To address information overload,
ISR-CSS provides the provision to filters and prioritize data according to end-user preferences. ISR-CSS dispenses
mission-critical and timely actionable information for end-user utilization, enabling faster response to a greater range of
threats across the mission spectrum.
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