Student project: Efficient indoor position tracking using UWB-IoT radar

Eindhoven - Master projects/internships
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More than two weeks ago
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Student project: Efficient indoor position tracking using UWB-IoT radar

 

What you will do

Nowadays, smart buildings are evolving to truly intuitive buildings. They will be equipped with a variety of sensing technologies to monitor different aspects within the building. Position tracking can be an initial point of many applications within smart buildings such as asset tracking, personnel situation, tracking and counting and health condition and many other applications. Due to the degraded performance of GPS in indoor environments, other measurement technologies are required for this aim. Radar sensors provide Low-power and low-complexity sensor realization for reliable human tracking in indoor environments.  In addition, radar sensors are also preferred over other image-based sensors due to privacy preservation and robustness to ambient light and heat conditions. At IMEC, an ultra-low power UWB-IoT radar front-end has been developed. In this project, a suitable indoor people tracking algorithm is going to be studied to achieve a low-power complete people sensing system by using the radar HW. An appropriate method should be investigated, analyzed and evaluated providing an acceptable trade-off between accuracy, complexity, and real-time performance requirement of the system.

Your tasks:

  • Literature survey on Bayesian filtering and data association techniques for radar system.
  • Initial study on current people tracking solutions designed at imec.
  • Investigate a low-power, accurate people tracking solution for UWB-IoT radar sensor.
  • System modeling and implementation of the proposed solution.
  • Thesis writing and technical documentation at imec-Holst Centre.

 

Who you are

  • You are a Master student in Electrical Engineering or a related field.
  • You are available for a period of 6 to 8 months.
  • Affinity with a hands-on approach.
  • Prior experience in statistical signal processing.
  • Prior experience with Matlab/Python.
  • Prior experience in Bayesian filtering is preferred.
  • Prior experience to work with FMCW radar system is a plus.
  • Entitled to do an internship in the Netherlands, Eindhoven.
  • Motivated student eager to work independently and expand knowledge in the field.
  • Good written and verbal English skills.

 

For internship opportunities at imec in Holst Centre, please visit the holst centre website: https://www.holstcentre.com/careers/thesis-opportunities/

 

Interested

Click on ‘apply’ to submit your application. You will then be redirected to e-recruiting.

Please be advised that non-EU/EEA country students that are studying outside of the Netherlands, need to have a work-permit to be able to do an internship in the Netherlands.

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