MATLAB and Simulink Training

Sensor Fusion and Object Tracking with MATLAB

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Course Details

This one-day course provides hands-on experience with developing and testing localization and tracking algorithms. Examples and exercises demonstrate the use of appropriate MATLAB® and Sensor Fusion and Tracking Toolbox™ functionality. Topics include:
  • Localization for orientation and position
  • Scene generation and sensor detection import
  • Filters and motion models
  • Data association
  • Multi-object trackers

Day 1 of 1

Localization for Orientation and Position

Objective: Fuse IMU and GPS sensor data to estimate position and orientation.

  • Model measurements from accelerometers, gyroscopes, magnetometers, and GPS.
  • Fuse sensor data to estimate the pose in terms of position, velocity, and orientation.
  • Visualize the pose estimation and plot platforms and trajectories.

Scene Generation and Detection Import

Objective: Import and process detections or generate scenarios used in multi-object trackers.

  • Preprocess and package collected sensor detections.
  • Create a tracking scenario with multiple sensors and platforms.
  • Define waypoint or kinematic trajectories.
  • Customize sensor parameters.
  • Generate detections used in sensor fusion algorithms.

Filters and Motion Models

Objective: Select and tune filters and motion models based on tracking requirements.

  • Evaluate filters against scenario requirements.
  • Compare and contrast different motion models.
  • Configure an Interacting Multiple Model (IMM) filter to track different maneuvers.

Data Association

Objective: Determine the appropriate data association method for different tracking situations.

  • Select from among Global Nearest Neighbor (GNN), Joint Probabilistic Data Association (JPDA), Track-Oriented Multiple Hypothesis (TOMHT), and other data association methods.
  • Determine how multiple detections are assigned to different tracks.

Multi-Object Trackers

Objective: Create multi-object trackers to fuse information from multiple sensors such as vision, radar, and lidar.

  • Configure trackers and parameters.
  • Perform track association and management.
  • Visualize the tracked objects.

Appendix A: Trackers for Passive Sensors

Objective: Create multi-object trackers and fusion systems that receive angle-only or range-only measurements from passive sensor systems.

  • Triangulate multiple line-of-sight detections.
  • Perform static fusion of passive synchronous sensor detections.
  • Track with range-only measurements.
  • Track with angle-only measurements.

Level: Intermediate


  • MATLAB Fundamentals or equivalent experience using MATLAB; basic knowledge of tracking concepts.

Duration: 1 day

Languages: English, 한국어

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