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Data Fusion Features


 DASDAF represents a significant improvement with respect to other classifiers and pattern analysis technologies.  Processing is done in three steps: (1) Agreement Map (AM) generation/fusion; (2) AM bitwise binary processing to remove isolated agreement events, fuse multiple training set exemplars related to the same or similar targets, etc.; (3) AM processing via ATR FIR filtering within the “pattern space.”  It is applicable to any sensor output that can be represented as a set of numerical values  regardless of sensor type, data structure or compression level.



  • Exploits archival & real-time target attributes
  • Supports embedded processing implementations
  • Adapts dynamically and  learns from experience
  • Employs highly efficient, parallel operations
  • Discloses Pattern Matching Process & results
  • Dynamically adaptive providing robustness in actual  applications
  • Parallel application of multiple classifiers to accurately identify observations and patterns
  • Solves problems related to dynamic data fusion, automatic recognition and classification in multi-sensor data streams
  • Correct classifications are Immediately visible with errors readily detected
  • About Dynamic Adaptive Sensor Data Fusion

    Examples of Dynamic Adaptive Data Fusion





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