Unified Bayesian Detection and Tracking in Hostile Radar Environments

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ00603C0120
Agency Tracking Number: 031-0606
Amount: $69,943.00
Phase: Phase I
Program: SBIR
Awards Year: 2003
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 R.K. Mehra/B.Ravichandran
 President/Manager R&D
 (781) 933-5355
Business Contact
 R.K. Mehra
Title: President
Phone: (781) 933-5355
Email: rkm@ssci.com
Research Institution
Scientific Systems Company, Inc. (SSCI) and its subcontractor LockheedMartin Tactical Systems (LMTS) propose to develop and demonstrate aconcept-feasibility algorithm capable of optimally detecting andtracking air and TBM targets in the presence of a hostile radarsensing environment such as background clutter, jamming, andElectronic Counter-Measures (ECM). We propose to do this by using anovel generalized recursive Bayes nonlinear filter in whichsingle-target detection has been fully, systematically, and rigorouslyunified with single-target tracking; and in which real-timealgorithmic implementation is accomplished using state-of-the-artparticle-systems filtering. The proposed work is partially based onbasic research in multisensor-multitarget data fusion, detection,tracking, and identification conducted by LMTS and funded over thelast six years by the U.S. Army Research Office. This work will alsobe greatly facilitated by existing development in nonlinear filteringand joint detection, tracking and discrimination being conducted bySSCI and LMTS for agencies such as the Missile Defense Agency and theAir Force Research Laboratory under four different R&D contracts. Themajor objectives of Phase I will be to: (1) provide a sound Bayesiannonlinear filtering paradigm for the general investigation of jointdetection and tracking in hostile sensing environments; (2) developnew Bayes-filter concept-feasibility algorithms which account fortarget non-existence, clutter, jamming, ECM, etc.; (3) performsimulation, analysis, and limited-complexity proof-of-conceptdemonstrations using simulated radar data; (4) select one or more ofthese candidates for further implementation in a potential Phase IIeffort; and (5) document the results in a Final Report.Phase II will emphasize the development of more sophisticatedprototype versions of the integrated data fusion and sensor resourcemanagement algorithms developed in Phase I. Commercial applicationsof the approach will also be investigated by SSCI and LMTS duringPhase I and fully developed during Phase II. Detection and tracking are someof the key technologies for global surveillance, precision strike, airsuperiority and defense, which are three of the seven science andtechnology thrust areas identified by the Director of Defense Researchand Engineering. The current limitations are due to poor understandingof how to model, fuse, and filter data from multiple sources. Theproposed R&D addresses all of these problems.

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

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