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Course Description

Short Course 14 hours 1.4 CEUs $3,795

Fundamentals of Multi-Target Tracking & Multi-Sensor Data Fusion training by Tonex is designed to provide an in-depth understanding of these two fields and their applications. It covers topics such as introduction to MTT, probability theory and Bayes’ rule, detection and tracking, data association, filtering and smoothing, and performance evaluation. It is suitable for professionals in defense, surveillance, robotics, and autonomous systems, and equips them with the skills and knowledge needed to develop effective tracking and fusion systems.

Multi-target tracking (MTT) is related to vision and signal processing that involves tracking multiple moving objects over time in a given scene. Participants will learn about MTT applications in various domains including defense, surveillance, autonomous driving, robotics, and object recognition. MTT aims to estimate the trajectories and states of multiple targets based on sensor measurements obtained from one or more sensors.

Multi-sensor data fusion systems combine information from multiple sensors to provide a more comprehensive and accurate understanding of the environment. Here are a few examples of multi-sensor data fusion systems in different application domains

Multi-sensor data fusion (MSDF) is a related field that deals with combining information from multiple sensors to improve the accuracy and reliability of target tracking systems. In many real-world scenarios, a single sensor may not provide sufficient information to accurately track targets due to occlusions, sensor limitations, or noisy measurements. By fusing data from multiple sensors, it becomes possible to overcome these limitations and obtain a more accurate and comprehensive understanding of the scene.

Course Outline

Course Topics
  • Introduction to Data and Sensor Fusion
  • Fundamentals of Multi-target Tracking (MTT)
  • Challenges with Multi-target Tracking (MTT)
  • Overview of Multi-sensor Data Fusion (MSDF)
  • Integration of Sensor Data
  • Multi-Sensor Data Fusion (MSDF) Architecture, Design, and Implementation
  • Architecture of a Multi-sensor Data Fusion System
  • Sensor Data Identification and Classification
  • Overview of Multi-Sensor Data Fusion (MSDF) Algorithms
  • Case Studies: Examples of Multi-Sensor Data Fusion Systems

Learner Outcomes

After completing this course, the students will be able to:
  • Define what Multi-target tracking (MTT) is
  • 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
  • Identify the motivating factors behind Multi-sensor data fusion (MSDF)
  • List the principal components of MTT and MSDF
  • 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

Duration

14 Hours | 2 Days or 4 Nights
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