Parameter estimation techniques for indoor localisation via WiFi

Abstract : In an indoor environment, the problem of extracting the Angle-of-Arrival of the Line-of-Sight component between a transmitter and Wi-Fi receiver using a SIMO link is the main concern of this thesis. One main challenge in doing so is due to the rich multipath channel that indoor environments enjoy. This is so because multipath results from the fact that the propagation channel consists of several obstacles and reflectors. Thus, the received signal arrives as an unpredictable set of reflections and/or direct waves each with its own degree of attenuation and delay. Other challenges are limitation of resources, such as number of antennas, available bandwidth, and Signal-to-Noise-Ratio; not to mention the Wi-Fi ”imperfections”, such as gain/phase mismatches between antennas and synchronisation issues between transmitter and receiver. In this thesis, our main focus is implementing a real-time system that could measure the angle between a transmitter and receiver in the presence of all challenges. In particular, we have taken into account all factors that perturb the Joint Angle and Delay estimation problem and formulated a system model accordingly. These factors are: Sampling Frequency offset (SFO), Carrier Frequency Offset (CFO), Phase and Delay offsets at each antenna. To compensate for the effect of these critical factors, we propose an offline calibration method to compensate for all their effects. This thesis will also include other theoretical methods that have to deal with Angle-of-Arrival Estimation problem from compressed sensing and signal processing point of views.
Complete list of metadatas

Cited literature [111 references]  Display  Hide  Download

https://pastel.archives-ouvertes.fr/tel-01740339
Contributor : Abes Star <>
Submitted on : Wednesday, March 21, 2018 - 7:16:07 PM
Last modification on : Wednesday, May 15, 2019 - 12:53:20 PM
Long-term archiving on : Thursday, September 13, 2018 - 8:21:19 AM

File

ThesisAhmadBazziwfrontpagecorr...
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01740339, version 1

Collections

Citation

Ahmad Bazzi. Parameter estimation techniques for indoor localisation via WiFi. Signal and Image processing. Télécom ParisTech, 2017. English. ⟨NNT : 2017ENST0051⟩. ⟨tel-01740339⟩

Share

Metrics

Record views

366

Files downloads

411