Using the Channel Impulse Response for Localization of Obstacles

Status: offen
Betreuer: Horst Hellbrück , Marco Cimdins
Student: n.a.

Themengebiet

Ultra-wideband (UWB) technologies such as IEEE 802.15.4a are leading candidates for indoor localization systems. The high bandwidth results in time resolutions in the nanosecond domain enabling localization accuracies below 0.5 m. Another advantage of UWB is that channel impulse responses can be easily measured and evaluated in terms of line-of-sight and non-line-of-sight components.

Details

There exist various and partially inter-dependent chirp parameters, e. g. center frequency, bandwidth and maximum detectable range, which can be adjusted to create a reasonable and valid chirp configuration. The chirp configuration is heavily dependent on the use case and the expected scene since distances, size and the number of objects as well as motions given different velocities and accelerations can be very different. Further limitations for adjusting the chirp parameters can arise due to hardware and regulatory constraints. In consequence, there is no perfect chirp configuration that fits all use cases. Chirp parameters have to be designed carefully with regard to the specific use case, application, and the expected scene the radar operates in. That's where this thesis proposal comes into the picture: This thesis aims to provide help for finding practical and reasonable chirp parameters for TI mmWave radars for different use cases and applications respectively.

Aufgaben

  • Modeling of the UWB channel impulse response via simulation
  • Evaluation of the UWB model with measurements
  • Mathematical description of the forward problem (known transmitter and receiver positions and positions of the walls/obstacles)
  • Derivation of the inverse problem
  • Evaluation of the inverse problem with simulation
  • Systematic evaluation of the inverse problem with UWB radio modules
  • Estimation of the boundaries (number of reflections, accuracies, noise, ...)

Voraussetzungen

  • Good knowledge of a high-level programming language (e.g. Python, Java, Matlab, C#)
  • Basic knowledge of statistics
  • Interest in radio applications and digital signal processing
  • Willingness to familiarize yourself with Decawave UWB devices
  • Independent and self-organized working