Please use this identifier to cite or link to this item: https://doi.org/10.3390/s19010087
Title: Imaging for small UAV-borne FMCW SAR
Authors: Hu, X 
Ma, C
Hu, R 
Yeo, T.S 
Keywords: Air navigation
Antennas
Motion compensation
Radar imaging
Synthetic aperture radar
Synthetic apertures
Unmanned aerial vehicles (UAV)
FMCW
Frequency-modulated continuous waves
Intra-pulse motion
Modified range-Doppler algorithm
Phase gradient algorithms
Range cell migration correction
Small unmanned aerial vehicles
Squinted azimuth-dependent PGA
Frequency modulation
Issue Date: 2019
Publisher: MDPI AG
Citation: Hu, X, Ma, C, Hu, R, Yeo, T.S (2019). Imaging for small UAV-borne FMCW SAR. Sensors (Switzerland) 19 (1) : 87. ScholarBank@NUS Repository. https://doi.org/10.3390/s19010087
Abstract: Unmanned aerial vehicle borne frequency modulated continuous wave synthetic aperture radars are attracting more and more attention due to their low cost and flexible operation capacity, including the ability to capture images at different elevation angles for precise target identification. However, small unmanned aerial vehicles suffer from large trajectory deviation and severe range-azimuth coupling due to their simple navigational control and susceptibility to air turbulence. In this paper, we utilize the squint minimization technique to reduce this coupling while simultaneously eliminating intra-pulse motion-induced effects with an additional spectrum scaling. After which, the modified range doppler algorithm is derived for second order range compression and block-wise range cell migration correction. Raw data-based motion compensation is carried out with a doppler tracker. Squinted azimuth dependent phase gradient algorithm is employed to deal with azimuth dependent parameters and inexact deramping, with minimum entropy-based autofocusing algorithms. Finally, azimuth nonlinear chirp scaling is used for azimuth compression. Simulation and real data experiment results presented verify the effectiveness of the above signal processing approach. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
Source Title: Sensors (Switzerland)
URI: https://scholarbank.nus.edu.sg/handle/10635/175095
ISSN: 1424-8220
DOI: 10.3390/s19010087
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