Learn about application of artificial neural network technology to data fusion for :
target recognition, airborne target recognition, activity-based intelligence, C4ISR, Electronic Warfare (EW), radar and EO-IR thermal imaging sensors, missile defense, cyber warfare, air, space and maritime surveillance, net-centric warfare, Activity-based Intelligence, effects-based operations process control, proactive maintenance and industrial automation.
Audience :
- Project managers
- Product managers
- Software and systems engineers
- EW and TDL operators
- Scientists
- R&D
- Military and law enforcement.
Learning Objectives:
- Define what data fusion approach is
- Identify the motivating factors behind data fusion
- Explain value proposition of data fusion
- Define the key features of data fusion and sensor integration
- List the functional requirements of multisensory fusion
- List the four pillars of data fusion and Multi-Sensor Data Fusion
- Understand what data fusion and its applications are
- List the principal components of data fusion systems
- Define Extracting, Transforming and Loading (ETL) operations
- Practice using the data fusion
- Select the right data fusion systems for your mission and application
- Assemble and manage information gathering and integration from a variety of sources
- Apply cutting-edge tools, methods and techniques for multi-sensor integration
- Explain application of multisensory fusion applied to identification, target tracking, net-centric, TDL, situational and threat assessment
Course Agenda:
- Introduction to Data Fusion
- Intelligence Analysis and Data Fusion
- Principles of Sensor Fusion
- Real-time Sensor Fusion
- Multi-Sensor Data Fusion
- Multi-level Data Fusion Modeling
- Multi-Sensor Data Fusion Architecture, Design and Implementation
- Classification of Data Fusion Techniques
- Data Fusion and Activity-Based Intelligence (ABI)
Call us today at +1-972-665-9786.
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