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Efficient Clutter Suppression and Nonlinear Filtering Techniques for Tracking…

Award Information

Agency:
Department of Defense
Branch:
Missile Defense Agency
Award ID:
Program Year/Program:
2013 / STTR
Agency Tracking Number:
B12B-004-0040
Solicitation Year:
2012
Solicitation Topic Code:
MDA12-T004
Solicitation Number:
2012.B
Small Business Information
Toyon Research Corp.
6800 Cortona Drive Goleta, CA -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2013
Title: Efficient Clutter Suppression and Nonlinear Filtering Techniques for Tracking Dim Closely Spaced Objects in the Presence of Debris
Agency / Branch: DOD / MDA
Contract: HQ0147-13-C-7415
Award Amount: $100,000.00
 

Abstract:

EO/IR elements of the Ballistic Missile Defense System (BMDS) responsible for detecting and tracking ballistic missile threats encounter extraordinarily challenging threat and scene phenomenology. Specifically, non-stationary clutter characteristic of airborne and satellite-based sensor systems, along with dim target signatures, closely-spaced objects, and dense debris clouds typical of ballistic threats in midcourse flight, present complications for accurately detecting, tracking, and engaging ballistic threats across the BMDS. Current Detect-then-Track algorithms are extremely vulnerable to high false alarm rates under these circumstances. At a system level, the problem is much more catastrophic; detections from multiple sensors overwhelm the system making multisensor integration difficult. Due to range deficiencies of EO/IR sensor technology, multisensor integration is vital for successful intercept of ballistic threats. To address these challenges, we propose a framework that leverages spatiotemporal image processing algorithms for non-stationary clutter estimation and rejection, and nonlinear filtering based Track-before-Detect algorithms for tracking dim targets. Our approach fuses information across sensors without loss of information due to detection thresholds. Our algorithms, when applied jointly, provide a near-optimal solution. In addition, our algorithms are capable of resolving dim closely-spaced objects and robustly handle nonlinearities from: threat trajectories, closely-spaced object/debris phenomenology, and 3D-to-2D projective nonlinearities typical of optical sensors.

Principal Investigator:

Tim Fair
Analyst
(703) 674-0612
tfair@toyon.com

Business Contact:

Marcella R. Lindbery
Director of Contracts
(805) 968-6787
mlindbery@toyon.com
Small Business Information at Submission:

Toyon Research Corp.
6800 Cortona Drive Goleta, CA -

EIN/Tax ID: 953526665
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
University of Southern California
Information Sciences Institute
4676 Admiralty Way
Marina del Rey, CA 90292-
Contact: Alexander Tartakovsky
Contact Phone: (213) 740-2450