Bayesian Tracking Algorithm(s) for Determining Highest Probability Predicted Intercept Points(s) in the AEGIS Combat System
Navy SBIR FY2018.1
Sol No.: |
Navy SBIR FY2018.1 |
Topic No.: |
N181-046 |
Topic Title: |
Bayesian Tracking Algorithm(s) for Determining Highest Probability Predicted Intercept Points(s) in the AEGIS Combat System |
Proposal No.: |
N181-046-0596 |
Firm: |
GCAS Incorporated 1531 Grand Avenue
Suite D
San Marcos, California 92078 |
Contact: |
Scott Woodson |
Phone: |
(760) 591-4227 |
Web Site: |
http://www.gcas.net |
Abstract: |
This Phase I project will demonstrate the use of a Bayesian-based tracker can be used to instantaneously addressing targets in raiding or swarming configurations and provide optimal engagement options to the Sailor. The proposed approach is to develop the tracking and engagement scheduling algorithms using customized tools for dynamic Bayesian Networks and Decision Influence Diagrams within a Probabilistic Relational Model framework. The tools will include the modeling of Second Order Uncertainty (SOU) in capturing and quantifying uncertainty in the provided target observations and the conditional probability processing elements used by the Bayesian-based tracker. The desired outcome of our Phase I Option effort will be a successful demonstration of the our SOU technology using a toy prototype simulation that identifies the highest probability Predicted Intercept Points with a threat scenario. The simulation can be exercised to demonstrate the interaction of the various relevant system elements (threat types, assumed capability of the incoming threat, number of threats, operational and test environment conditions, clutter and debris) that have the highest probability of kill. This includes establishing the confidence/uncertainty levels when predicting performance of the modelled system |
Benefits: |
The immediate Phase III application for this technology is in support of PEO IWS-1in transitioning the prototype tracking software applications to allow for further experimentation and refinement. The prototype tracking software application will be incorporated into the AEGIS baseline testing modernization process. This will consist of integration into a baseline definition, incorporation of the baselines existing and new threat capabilities, validation testing, and combat system certification. There are numerous long-range commercial applications for the tracking algorithms including adaptation to internal avoidance control system of UAVs/drones and other autonomous vehicles, assistance to air traffic controllers in monitoring potential collisions, and security/ police applications for monitoring unwanted external monitoring by UAVs. |
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