3D Mapping of Underground Utility Networks Using Ultra Wideband Multi-Antenna Array Step Frequency Radar

EasyChair Preprint 5637

Abstract

This thesis work aims at development of an Ultra Wide Band (UWB) multi antenna array Step Frequency Radar (SFR) system and necessary signal processing steps required for detection, localisation and classification of underground utility networks. The system shall equip linear antenna array to cover the entire width of the road or the survey channel at optimal high speed suitable for highway and local urban roads. Moreover, it shall be capable of producing multiple parallel B-scans (radar image representation). The thesis was inspired as the solution to recently introduced government regulations in maintaining the geomatics database about the underground utility networks and positioning standards as a damage prevention measures during excavations. For example, class A, precision of three-dimensional position of sensitive buried networks is 11.25 cm as bound in NF-S70-003-2 standard in France. On the other hand, the solution must be very robust in highly dynamic, complex, unpredictable, dispersive subsoil environment which is suggested by the nature of this application. We have split the vast objective into two different sub tasks such as SFR system prototyping with data acquisition software development; and signal processing techniques for automatic pipe detection, depth and diameter estimation provided that the localisation accuracy meets the expectation of Class A precision. Hence, the prospective signal processing methods are highly oriented on Machine learning and computer vision based AI algorithms combined with other physical signal processing techniques.

Keyphrases: GPR, Utility Mapping, machine learning, signal processing, step-frequency radar

@booklet{EasyChair:5637,
  author    = {Mohamed Jaufer Rakeeb},
  title     = {3D Mapping of Underground Utility Networks Using Ultra Wideband Multi-Antenna Array Step Frequency Radar},
  howpublished = {EasyChair Preprint 5637},
  year      = {EasyChair, 2021}}