Agenda

MSc SS Thesis Presentation

• Thursday, 17 October 2019
• 10:00-10:45
• HB 21.120

Indoor localization using narrowband radios and switched antennas in indoor environment

In this thesis, we explore the potential of indoor localization using Bluetooth narrowband radios. To start with, a data model according to the property of the conducted measurement data is developed. The conducted measurement data is radio channel measure- ments based on channel sounding technique. Then the data model is developed as a channel impulse response model and multipath signals are indicated by different time delays.

Delays are estimated after subspace estimation of the data covariance matrix. Smoothing techniques are employed to improve the covariance matrix estimate. To detect the rank of the subspace, two techniques are investigated, namely the MDL algorithm and the threshold method. New estimates for the thresholds are derived, valid for Hankel-structured data matrices. Experiments are conducted to investigate the performance and reliability of those two techniques, under different parameter values.

Next, we consider subspace-based super-resolution algorithm, in particular the MUSIC algorithm. The functionality of the MUSIC algorithm on narrowband radios measurements is tested and evaluated firstly by simulation experiments, which demonstrate the practicability of applying MUSIC algorithm on narrowband radios measurements. Then experiments are extended to the measurement data that conducted from real indoor environments, for the purpose of indoor localization realization using narrowband radios.

Overview of MSc SS Thesis Presentation