Signal Processing and Speech Communication Laboratory
hometheses & projects › Target Detection in Automotive Radar Signals

Target Detection in Automotive Radar Signals

Status
In work
Type
Bachelor Project
Announcement date
17 Oct 2019
Student
Thomas Mayerwieser
Mentors
Research Areas

Short Description:

Radar systems provide information about object distances, velocities and positions. Object detection is a safety critical task for automotive applications such as Advanced Driver Assistance Systems (ADAS) or autonomous driving. The time domain signal as received by an FMCW/CS radar system is processed according to the typical radar signal processing chain; the result is a range-Doppler Map. These data contain peaks at the observed object’s distances and velocities together with noise and clutter.

The task is to implement different object detection algorithms (baseline and state-of-the-art) and compare their performance using task-dependent evaluation metrics. You will work with real world measurements that were collected by our team in August 2019. The measurements don’t contain ground truth (= manual labels), so you might need to label some of the data in order to perform the evaluation.

Requirements:

  • Good programming skills in Python
  • Interest in code quality, code reusability and systematic evaluation