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Course Overview

The Ansys HFSS for Advanced Driver-Assistance Systems (ADAS) course demonstrates the Ansys solution for autonomous vehicles from Radar design to dynamic scenario modeling. This course is designed for intermediate-advanced users and includes four modules with workshops that shows the workflows from start to finish. Topics such as Radar sensor design (single element and array analysis), Radome Unit Cell analysis and the impact of Radome on Radar array performance, Radar module and fascia interaction, and Radar scene analysis using chirp by chirp simulation and accelerated doppler processing (ADP) are explored in this course.

Prerequisites

  • Prior knowledge of Ansys HFSS 3D Components, Boundary Conditions, Ports and Mesh Course, Ansys HFSS for Antenna Design Course, and Ansys HFSS SBR+ Antenna Placement Course are required.
  • Knowledge of antenna design and relevant parameters including S-parameters and Far-Filed patterns are highly recommended.
  • Knowledge of antenna impedance matching, finite array principles, hybrid solutions, ACT Extensions, and Radar parameters and specifications are also important as workshops utilize these engineering principles.

Target Audience

Antenna Designers and Radar Engineers

Teaching Method

Lectures and hands-on simulation workshops to develop familiarity and productive skill in analyzing Radar antenna arrays and Radar scenarios using HFSS. Although the course listing is instructor led, the simulation workshops are self-explanatory and easy to follow for independent learners.  A training certificate is issued on completion of the course.

Learning Path

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Learning Outcome

Following completion of this course, you will be able to:

  • Import 3D Component model and view/modify parametric variables.
  • Work with Source Contexts in Edit Sources to view the beam pattern of each antenna element in the array.
  • Define and analyze the Radome Unit Cell and run parametric analysis.
  • Evaluate the impact of Radome geometry on its EM performance by monitoring transmission and reflection coefficients versus frequency. 
  • Set up the antenna array module with either simplified Radome or real Radome.
  • Apply Hybrid solutions such as FEM-IE and FEM-SBR+ for electrically large problems (Radar module and fascia interaction) and assess the effects of Hybrid Regions. 
  • Apply RadarPre/RADARpost ACT Extensions to generate the driving scene and Range-Doppler map.
  • Work with Radar parameters and modify them for the desired Radar scene. 
  • Apply MoveIt ACT Extension to generate the driving scene.
  • Define the Radar module with Ideal antenna pattern (parametric beam) and Real antenna pattern for ADAS scene.
  • Import a walking human model and view the animated scene versus time.
  • Set up Range-Doppler configuration and Radar specifications for Accelerated Doppler Processing (ADP) simulation. 
  • Generate parametric setup to create both dynamic ADAS scene and animated Range-Doppler map.

Available Dates

Currently, no training dates available

Learning Options

Training materials for this course are available with a Ansys Learning Hub Subscription. If there is no active public schedule available, private training can be arranged. Please contact us.

Agenda

This is a 1-day classroom course covering both tutorials and workshops. For virtual training, this course is covered over 2 x 2 hour sessions. Module 1 Introductory workshops provide antenna-related HFSS familiarity; they should be completed independently prior to the start of class.

Virtual Classroom Session 1 

  • Module 0: Lecture0 Introduction to ADAS
  • Module 1: Workshop1.1 Radar Sensor Design _ Single Element, Workshop1.2 Radar Sensor Design _ Array
  • Module 2: Workshop2.1 Radome Unit Cell, Workshop2.2 Radar Radome Analysis

Virtual Classroom Session 2 

  • Module 3: Workshop3.1 Radar Module and Fascia Analysis  
  • Module 4: Lecture4 Radar Scene Analysis, Workshop4.1 Radar Scenario _ Chirp by Chirp, Workshop4.2 Radar Scenario_ Accelerated Doppler Processing, Workshop4.3 Walking Human _ Accelerated Doppler Processing