The development of a drone radar system
File(s)
Author(s)
Carpenter, Anthony
Type
Thesis
Abstract
Interferometric Synthetic Aperture Radar (InSAR) is an active remote sensing technique capable of quantifying millimetric rates of earth surface and structural deformation. Coupled with emerging drone technologies, there is scope for improved spatial and temporal resolutions in the InSAR data. The former is desired for small and complex sites such as nuclear power stations, whilst the latter would provide more comprehensive and flexible time-series analyses. This thesis details the hardware, software, and experimental development of a drone radar system, capable of providing Synthetic Aperture Radar (SAR) imaging for future developments and applications utilising InSAR. These developments are at the forefront of this novel field of research, with few authors demonstrating similar miniaturised radar systems with SAR capabilities. The hardware development includes a custom drone radar payload, with a combination of commercially available and custom components; the latter includes radar antennas manufactured from Copper Clad Laminate (CCL) and tested in an anechoic chamber. Similarly, a range of third party and custom software is tested and developed, including Frequency Modulated Continuous Wave (FMCW) radar in GNU Radio Companion (GRC), and SAR processing in MATLAB. A laboratory experiment is devised to test and demonstrate the hardware and software components, and explore the effect of varied moisture content of a generic topsoil on the phase of InSAR interferograms using Software Defined Radar (SDR). Lastly, a case study is presented for an active landslide adjacent to the M25, where both satellite InSAR and the drone radar system are demonstrated. Importantly, this thesis presents the first SAR image produced using the drone radar system, with clearly defined targets and an improved spatial resolution compared to satellite SAR. Ongoing and future work seeks to expand upon these developments and transition from discrete drone SAR imaging to automated drone InSAR hazard detection.
Version
Open Access
Date Issued
2024-03-16
Date Awarded
01/03/2025
License URL
Advisor
Lawrence, James
Mason, Philippa
Ghail, Richard
Sponsor
Engineering and Physical Sciences Research Council
Grant Number
EP/L015900/1
Publisher Department
Department of Civil and Environmental Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)