Advanced Data Association and Predictive Tracking (ADAPT)

Period of Performance: 02/28/2008 - 08/27/2008

$99.5K

Phase 1 SBIR

Recipient Firm

Decisive Analytics Corp.
1400 Crystal Drive Array
Arlington, VA 22202
Principal Investigator

Abstract

A high-quality SIAP is the essential foundation of effective air defense, reliable combat identification and is the key to exploiting advanced offensive capabilities. To develop an effective SIAP, the tracking and fusion algorithms must overcome real-world challenges such as high target density, heterogeneous data sources, and communication bandwidth requirements. The DECISIVE ANALYTICS Corporation (DAC) team proposes to overcome these real-world problems through an innovative algorithm that has the potential to vastly improve the quality of measurement association, track correlation and fusion of sensor data with large uncertainty (e.g. high-density, passive sensors, electronic countermeasures, etc.). We propose to perform heterogeneous data fusion via a state-of-the-art fusion algorithm which will naturally and easily accommodate new and diverse sensor types as well as unanticipated sensor behavior in the face of increasingly difficult scenarios. Application of the proposed algorithms has been shown to produce fewer mis-associations and better run-time performance than other advanced tracking algorithms. Indeed, this innovative solution has garnered a commercial backing from Raytheon who has agreed to endorse the DAC team s solution through Phases I, II, and III.