SBIR/STTR Research Award
Integrated Fusion Performance Evaluation Theory and Applications
Award amount
$100,000Program and phase
SBIR · Phase IAward year
2007Award details
- Awarding agency
- Department of Defense
- Branch
- Air Force
- Recipient company
- MRLETS TECHNOLOGIES, INC.
- Proposal award date
- 2007-05-08
- Contract end date
- 2008-02-29
- UEI
- Not reported
- Solicitation number
- 2007.1
- Topic code
- AF071-232
Research abstract
Currently the Air Force is seeking theoretic support for the evaluation effort on fusion based surveillance systems. This evaluation will not be limited to isolated tracking or ATR functions; rather it will cover all the fusion functions in a unified manner. MRLets Technologies proposes an integrated fusion performance evaluation theory as a solution to this request. As the framework of the integrated fusion evaluation, 24 possible fusion architectures are analyzed in order to formulate the distribution of fusion result. Based on this development, we propose to approximate the distribution of the fusion system under evaluation with a multi-mode fusion performance model. As part of the model, a Markovian Urban System Transition Model (MUSTM) is proposed to represent the dynamics in a fusion environment. Along this line, we also propose a novel multispectrum sensor model to represent the sensor suite operating on spreading wave bands. The proposed fusion performance model also enables a set of new performance metrics that are invariant in nature and can better illustrate the trend of the performance of a fusion system. The proposed evaluation theory will be implemented into a software package so that it can be integrated into the fusion evaluation systems and sensor information exploitation programs of the Air Force, such as SAVig and FITE.
Technology keywords
Not reported
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Performance Monitoring and Prediction for Active Management of Distributed Sensors Fusion in Target Tracking
- Performance Evaluation Modeling for Multi-Sensor ATR and Tracking System
- Tracking Performance Self-Determination and Prediction for Sensor Data Fusion and Resource Management