Ladar Algorithm for Lethal Objects (LALO)

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,996.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
N00178-04-C-3072
Agency Tracking Number:
B041-013-0586
Solicitation Year:
2004
Solicitation Topic Code:
MDA04-013
Solicitation Number:
2004.1
Small Business Information
AERO OPTICS, INC.
655 Deep Valley Drive, Suite 335, Rolling Hills Estate, CA, 90274
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
625432679
Principal Investigator:
G. Newton Freeman
Principal Investigator
(310) 541-1933
gnf@aero-optics.com
Business Contact:
G. Freeman
President
(310) 541-1933
gnf@aero-optics.com
Research Institution:
n/a
Abstract
Advanced interceptor seekers with active ladar systems offer enhanced capabilities for target acquisition, discrimination, tracking, and targeting of a lethal object within a ballistic missile threat train including off-nominal threats and countermeasures. Full exploitation of these capabilities requires robust ladar algorithms to enhance seeker decision functions that include far-range ladar cuing, target acquisition/tracking, optimum handover, enhanced discrimination, aimpoint selection, and end game countermeasure mitigation. Algorithms are required to support laser augmentation of multiband passive sensors including non-coherent/coherent systems and active/passive fusion for improved seeker performance including mitigation of diffuse-scattering and laser-speckle effects. The proposed investigation will evaluate competing seeker/algorithm concepts through end-to-end dynamic simulation of a ballistic missile threat train as perceived over time by the interceptor seeker. The simulation will include the position/orientation dynamics and passive/active signatures of lethal/non-lethal objects and the associated seeker/algorithm response for acquisition, discrimination, tracking, and targeting of the lethal object. The investigation will consider realistic threat ensembles, deployment sequences, and background conditions to ensure algorithm robustness.

* information listed above is at the time of submission.

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