The intent of this investigation is to replace the low fill
factor visible sensor of a Cellular Neural Network (CNN) processor
with an InGaAs Focal Plane Array (FPA) using both bump bonding
and epitaxial layer transfer techniques for use in the Ballistic Missile
Defense System (BMDS) interceptor seekers. The goal is to fabricate
a massively parallel digital processor with a local as well as a global
interconnect architecture. Currently, this unique CNN processor is
capable of processing a target scene in excess of 10,000 frames per
second with its visible sensor. What makes the CNN processor so
unique is that each processing element includes memory, local data
storage, local and global communication devices and a visible sensor
supported by a programmable analog or digital computer program.
Missile Defense Agency/Advanced Systems, in partnership with both EUTECUS/University of Notre Dame (UND) and ITN Energy Systems/University of Central Florida (UCF) has embarked on developing a multispectral imaging IR sensor. This technology, when matured, could revolutionize IR sensor technology by reducing the need for cooling, eliminating lattice matching and avoiding epitaxial fabrication processes. This paper describes the approaches employed by both EUTECUS/UND and ITN/UCF teams to integrate nano-antenna technology with the existing cellular neural network (CNN) processor to produce multispectral IR sensors. This effort is a leap into the performance realm where biological systems operate.