Efficient Clutter Suppression and Nonlinear Filtering Techniques for Tracking Dim Closely Spaced Objects in the Presence of Debris

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-13-C-7415
Agency Tracking Number: B12B-004-0040
Amount: $100,000.00
Phase: Phase I
Program: STTR
Awards Year: 2013
Solicitation Year: 2012
Solicitation Topic Code: MDA12-T004
Solicitation Number: 2012.B
Small Business Information
6800 Cortona Drive, Goleta, CA, -
DUNS: 054672662
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Tim Fair
 Analyst
 (703) 674-0612
 tfair@toyon.com
Business Contact
 Marcella Lindbery
Title: Director of Contracts
Phone: (805) 968-6787
Email: mlindbery@toyon.com
Research Institution
 University of Southern California
 Alexander Tartakovsky
 Information Sciences Institute
4676 Admiralty Way
Marina del Rey, CA, 90292-
 (213) 740-2450
 Nonprofit college or university
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.

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

Agency Micro-sites

SBA logo
Department of Agriculture logo
Department of Commerce logo
Department of Defense logo
Department of Education logo
Department of Energy logo
Department of Health and Human Services logo
Department of Homeland Security logo
Department of Transportation logo
Environmental Protection Agency logo
National Aeronautics and Space Administration logo
National Science Foundation logo
US Flag An Official Website of the United States Government