DASDAF is a pattern recognition paradigm that combines sensor data and contextual scenario information to form an accurate picture of a battlespace or target
Features
Exploits prior & learned knowledge of target attributes
Supports embedded processing implementations
Dynamically adaptive and learns from experience
Employs highly efficient, parallel operations
Fully Discloses Pattern Matching Process & Results
Benefits
Parallel application of multiple classifiers to RADAR and/or EO/IR sensor data to identify probable target type/ track/location
Solution for problems related to dynamic data fusion, automatic target classification, and pattern recognition in disparate multi-sensor video imagery/data.
Applicable to any sensor output that can be represented as a set of numerical values regardless of sensor type, data format, or data compression
