Sensor Fusion and Tracking for Autonomous Systems

This white paper demonstrates how you can use MATLAB® and Simulink® to:

1. Define scenarios and generate detections from sensors including radar, camera, lidar, and sonar

2. Develop algorithms for sensor fusion and localization

3. Compare state estimation filters, motion models, and multi-object trackers

4. Perform what-if analysis with different scenarios

5. Evaluate positional accuracy and track assignment performance versus ground truth

6. Generate C code for rapid prototyping

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Explore our solutions on Automated Driving

Download this white paper to learn about Sensor Fusion and Tracking for Autonomous System

  • With this workflow, you can avoid reinventing the wheel with every new autonomous system development project,
    saving you time and effort. In addition, you can share your models and results both within and outside your
    organization.
  • In this white paper, Sensor Fusion and Tracking Toolbox™ and Automated Driving Toolbox™ are used in the associated
    workflows.
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White Paper: What’s New in MATLAB and Simulink for ADAS and AD

Learn more about the trends for Automated Driving and ADAS

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Using MATLAB and Simulink, you can focus your efforts on developing more advanced decisions and planning algorithm. Explore set of products for automated driving.

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