Influence of Discrimination Capability on Sensor Task Planning

The US Missile Defense Agency (MDA) is presented with many challenges in integration of diverse set of sensors previously developed by US agencies as well as new sensors into an effective, layered sensor network for missile defense. The Quality Equation Sensor and Element Tasking System (QUESETS) concept will help the MDA deal with the challenge of tasking this sensor network. QUESETS is derived from mature methodologies that has been used to task US military intelligence, surveillance and reconnaissance (ISR) sensors. QUESETS involves construction of a discrimination information scale (object recognition scale), development of quality equations for each sensor and sensor mode (e.g. narrow and wideband). These quality equations will predict information discrimination capability for each sensor and provide look-ahead estimates that predict discrimination performance to support the human operator in optimizing the tasking of BMD sensors. A QUESETS quality equation relates sensor discrimination capability on an information discrimination scale to engineering collection (e.g. geometry) and quality parameters (e.g. resolution, impulse response, signal-to-noise, signal-to-background). This approach requires much less computation than high fidelity simulation and optimization and can meet the timelines for BMD planning and engagement operations. The QUESETS approach has ready commercial applications for assessing digital information transmission losses.