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Track Refinement from Off-Nominal Break-Up

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-16-C-7712
Agency Tracking Number: B2-2230
Amount: $1,498,774.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: MDA14-003
Solicitation Number: 2014.2
Timeline
Solicitation Year: 2014
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-06-30
Award End Date (Contract End Date): 2019-09-12
Small Business Information
5024 Technology Parkway, Fort Collins, CO, 80528
DUNS: 956324362
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jason Johnson
 (970) 207-2245
 jason.johnson@numerica.us
Business Contact
 Jeff Poore
Phone: (970) 207-2211
Email: jeff.poore@numerica.us
Research Institution
N/A
Abstract
To achieve MDAs mission, it is crucial that the BMDS be able to acquire and maintain accurate tracks on objects produced by a missile launch over the lifetime of the threat.Certain missile events, such as break-ups and intercepts, have the potential to adversely affect the quality of situational awareness provided by the BMDS.Therefore, Numerica Corporation proposes an advanced optimization and estimation solution for track refinement over a broad range of off-nominal break-up scenarios, including passive rotational effects, impulsive break-ups, compound break-ups involving multiple closely spaced events, and break-ups precipitated by the collision of two objects.Our solution is founded on fundamental principles of physics, estimation theory, and methods of non-convex and combinatorial optimization. In particular, our approach is robust to the existence of sub-optimal local minima of the track refinement problem and is able to identify ambiguous solutions.Our approach also addresses the joint track refinement and data association problem, thereby achieving improved association of ambiguous data near the break-up or collision event. Numerica plans to coordinate with MDA and a prime contractor for a program of record to demonstrate our proposed approach using operationally relevant data.

* Information listed above is at the time of submission. *

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