
Multi-fovea Parallel Sensor-processor Architectures and Algorithms for UAV PlatformsAward last edited on: 11/12/2018
Sponsored Program
SBIRAwarding Agency
DOD : NavyTotal Award Amount
$899,985Award Phase
2Solicitation Topic Code
N111-063Principal Investigator
Csaba RekeczkyCompany Information
Phase I
Contract Number: N00014-11-M-0176Start Date: 5/9/2011 Completed: 9/8/2012
Phase I year
2011Phase I Amount
$149,995Benefit:
The steadily growing market of intelligence, surveillance and reconnaissance (ISR) in the military domain calls for new ways and methods to improve future generation of sensors. A growing trend is that the improvement of sensing/acquisition methods is conducted in parallel with embedding more intelligence near or close to the sensor. The anticipated results of the current work will enable creating a product (an advanced ultra-high-speed analytics sensor) usable on UAV/UGV platforms. The benefits for the military customer will be reduced SWaP and improved on-board video analytics capability which is minimal today. On the other hand, the ultra-high-speed imaging capability combined with stabilization, and on-board recognition capabilities are expected to be broadly exploitable in automotive applications and commercial UGVs. The real-time feature/signature analysis, event recognition and sense-and-avoid functions are also key to the broader emergence of intelligent commercial UAV platforms for flood and fire defense, vegetation classification, large area security surveillance and traffic monitoring.
Keywords:
Terrain recognition, Terrain recognition, Massively parallel algorithms. ,, Image Stabilization, Near/close sensor feature extraction, Sense and Avoid, Automatic Target Recognition, Multi-fovea processing, , Multi-core sensor-processor architecture
Phase II
Contract Number: N00014-12-C-0335Start Date: 5/23/2012 Completed: 12/30/2013
Phase II year
2012Phase II Amount
$749,990Benefit:
The steadily growing market of intelligence, surveillance and reconnaissance (ISR) in the military domain calls for new ways and methods to improve future generation of sensors. A growing trend is that the improvement of sensing/acquisition methods is conducted in parallel with embedding more intelligence near or close to the sensor. The anticipated results of the current work will enable creating a product (an advanced ultra-high-speed analytics sensor with embedded processing) usable on UAV/UGV platforms. The benefits for the military customer will be reduced SWaP and improved on-board video analytics capability which is minimal today. On the other hand, the ultra-high-speed imaging capability combined with stabilization, and on-board recognition capabilities are expected to be broadly exploitable in automotive applications and commercial UGVs. The real-time feature/signature analysis, event recognition and sense-and-avoid functions are also key to the broader emergence of intelligent commercial UAV platforms for flood and fire defense, vegetation classification, large area security surveillance and traffic monitoring.
Keywords:
Massively parallel algorithms. , Automatic target recognition, Terrain recognition, Near/close sensor feature extraction, Sense and avoid, Image stabilization, Multi-core sensor-processor architecture, Multi-fovea processing