Preprocessing Method for Enhanced Aiming and Discrimination

To address the MDA need to improve the performance of bulk filtering against nonthreatening flying objects, POC proposes to develop a new Preprocessing Method for Enhanced Aiming and Discrimination (PreMFEAD). This proposed technology is based on signal conditioning and statistical processing. The innovation in PreMFEAD will enable reliable and fast target acquisition, identification, and aiming, while performing target discrimination of multiple threatening and nonthreatening flying objects. As a result, this technology offers advantages not only in successful interception by rapid discrimination of explosive warheads from chuffing, deployment debris, and electronic countermeasure chaff, but also in increasing situational awareness by sifting nonthreatening clutter primitives out of radar signals, which directly address the MDA requirements. In Phase I, POC will demonstrate the feasibility of PreMFEAD by developing a new radar preprocessing system that is easily adaptable to a wide range of sensors (e.g., infrared) and applying it to simulated data. In Phase II, POC plans to further refine and optimize PreMFEAD to increase the system"s performance margins and demonstrate technology viability in a realistic environment using emulated data sets from multiple sensors. At the end of Phase II, the PreMFEAD system performance will be demonstrated in simulated cluttered and countermeasure combat environments.