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Data fusion

 Data Fusion : October 19th & 20th, 2011 - Online Registration          

Topic :  

Advanced multi-sensor data fusion. 
Location :    Paris

Target Audience :

 

  

This seminar is intended for scientists, engineers, software professionals and technical managers in defense and other industries who need to develop solutions to difficult fusion and decision-making problems.

Instructors :

 

  

Dr. Subrata Das

Machine Analytics : Founder & President

Dr. Kamel Mekhnacha

Probayes : Founder and CTO

Description :

 

 

 

 

 

 

 

 

  

Advances in systems provide today’s warfighter with a significantly larger, much more enhanced scope of the battlefield. However, with these new capabilities comes the ever-more pressing need to combine the increasing number of different and dispersed sources into a comprehensive picture of the battlespace. This training provides a detailed understanding of the cutting-edge and most commonly used technologies for multisensor data fusion. Specific questions to be answered:

  • How do requirements for low vs. high-level fusion differ?
  • What are the current trends and state-of-the-art in the data fusion area?
  • What are the drivers for multi-sensor data fusion in urban operations, bioterrorism, and missile defense?
  • How are net-centric and effects-based operations driving the developing of new tools and techniques?
For more information, click here.

Registration :

 

 

  

To register, 2 options : 

Detailed program

-       Lesson 1: Multi-Sensor Data Fusion

Key Issues in Multi-Sensor Data Fusion, Low vs. High Level Fusion, Sensor Types and Characteristics, Impact of Sensor Types on Fusion System Design.

-       Lesson 2: Architectures for Multi-Sensor Data Fusion and Decision Making

Joint Directorate of Laboratories (JDL) Architecture, Observe-Orient-Decide-Act (OODA) Loop, Situational Awareness vs. Situation Assessment, Cognitive Architectures.

-       Lesson 3: Multi-Sensor Data Fusion Application Domains

Conventional Warfare, Military Operations in Urban Terrains (MOUT), Bioterrorism, Theater Missile Defense, Air Operations Center (AOC) Operations, Effect-based Operations (EBO), System Status and Healthy Monitoring.

-       Lesson 4: Foundational Techniquesfor Handling Uncertainty

Bayesian Probability, Possibility Theory and Fuzzy Logic, Dempster-Shafer Theory of Belief Functions, Certainty Factor, Handling of Confidence.

-       Lesson 5: Level 1 and Level 2 Fusion

Gating and Data Association, Single and Multi Target Tracking, Interacting Motion Models, Kalman Filtering for Level 1 Fusion, Unit Aggregation via Spatiotemporal Clustering, Static and Dynamic Bayesian Belief Networks for Situation Assessment, Follow-On Threat Assessment and Course-of-Action Generation, Sensitivity Analysis and Collection Management, Agent-Based Information Fusion

-       Lesson 6: Decision Making in Uncertain Environment

Expected Utility Theory, Rule-Based Expert Systems, Influence Diagrams, Symbolic Argumentation and Aggregation, Measurement of Experts’ Consensus.

-       Lesson 7: Temporal Modeling for Multi-Sensor Data Fusion

State Space Model, Hidden Markov Model, Dynamic Belief Networks, Rao-Blackwellised Filtering, Extended and Unscented Kalman Filtering, Particle Filtering.

-       Lesson 8: Measuring Performance

Hit Rate, False Alarms, ROC Curve, etc., Subjective Evaluation, Cramer-Rao Lower Bound.

-       Lesson 9: Network Centric Warfare and Distributed Fusion

Publish and Subscribe Architecture, Pedigree Meta-Data Handling, Distributed Multi-Agent Fusion, Shared Situational Awareness, Distributed Sensor and Resource Management, Sense and Respond Logistics.

-       Lesson 10: Key Directions for Future Multi-Sensor Data Fusion

Data Mining / Machine Learning, Handling Unstructured Text Data, Knowledge Acquisition, Human Role in Data Fusion Process, Visualization, Semantic Web.

                                                               

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