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A system was assembled to study several aspects of locating
ship targets from infrared imagery. The system was either placed on
shore sites or installed on an aircraft to collect data on the
scene. The primary sensor was an infrared camera which produced
images of the scene at standard RS-l70 rates. Requirements that
included real time operation dictated the use of a parallel architecture
for this task. As no suitable commercial systems were avail
able, a custom array of bit slice microprocessors was assembled for
the task. Through extensive field tests strengths and limitations of
the design have been identified. These lessons are being applied to
the development of next generation systems.
A gimbal mounted infrared camera with digitization circuitry
presents a new 256 by 256 pixel image to the parallel pipelined
array of 17 bit slice microprocessors thirty times a second. To
extend processor performance beyond the standard commercial microprocessors.
two basic bit slice designs were employed. The bit slice
machines were highly tuned for the assigned tasks and algorithms.
Unfortunately this restricted the desired flexibility to readily
examine alternate algorithms. The fundamental architecture concept
performed well quickly reducing the large array of data to manageable
set of information. Real time operator displays were driven to
monitor the progress of each test run.
Results of the system operation were stored on video and digi
tal recorders permitting more detailed analysis after each test. Non
real time data reduction provided many insights into the system
operation and to algorithm improvements. Substantial operator interaction.
and data interpretation was required greatly slowing the post
test analysis phase. Overwhelmed with data, the analysts focused on
locating a few data segments of interest. Significant work remains
in improving the interfaces between the field data and the powerful
laboratory computers. Automation of the data analysis is also needed
to efficiently evaluate the great volume of field information.
Continuing improvements in Artificial Intelligence, Expert Systems,
Neural Networks, and other areas may help here.
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