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
Amount:
$100,000.00
Award Year:
2013
Program:
STTR
Phase:
Phase I
Contract:
HQ0147-13-C-7415
Award Id:
n/a
Agency Tracking Number:
B12B-004-0040
Solicitation Year:
2012
Solicitation Topic Code:
MDA12-T004
Solicitation Number:
2012.B
Small Business Information
Toyon Research Corp. (Currently TOYON RESEARCH CORPORATION)
6800 Cortona Drive, Goleta, CA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
054672662
Principal Investigator:
Tim Fair
Analyst
(703) 674-0612
tfair@toyon.com
Business Contact:
Marcella Lindbery
Director of Contracts
(805) 968-6787
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

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government