TY - JOUR
T1 - P-Band UAV-SAR 4D Imaging
T2 - A Multi-Master Differential SAR Tomography Approach
AU - Wang, Zhen
AU - Wei, Yangkai
AU - Ding, Zegang
AU - Zhao, Jian
AU - Sun, Tao
AU - Wang, Yan
AU - Li, Han
AU - Zeng, Tao
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/5
Y1 - 2023/5
N2 - Due to its rapid deployment, high-flexibility, and high-accuracy advantages, the unmanned-aerial-vehicle (UAV)-based differential synthetic aperture radar (SAR) tomography (D-TomoSAR) technique presents an attractive approach for urban risk monitoring. With its sufficiently long spatial and temporal baselines, it offers elevation and velocity resolution beyond the dimensions of range and azimuth, enabling four-dimensional (4D) SAR imaging. In the case of P-band UAV-SAR, a long spatial-temporal baseline is necessary to achieve high enough elevation-velocity dimensional resolution. Although P-band UAV-SAR maintains temporal coherence, it still faces two issues due to the extended spatial baseline, i.e., low spatial coherence and high sidelobes. To tackle these problems, we introduce a multi-master (MM) D-TomoSAR approach, contributing three main points. Firstly, the traditional D-TomoSAR signal model is extended to a MM one, which improves the average coherence coefficient and the number of baselines (NOB) as well as suppresses sidelobes. Secondly, a baseline distribution optimization processing is proposed to equalize the spatial–temporal baseline distribution, achieve more uniform spectrum samplings, and reduce sidelobes. Thirdly, a clustering-based outlier elimination method is employed to ensure 4D imaging quality. The proposed method is effectively validated through computer simulation and P-band UAV-SAR experiment.
AB - Due to its rapid deployment, high-flexibility, and high-accuracy advantages, the unmanned-aerial-vehicle (UAV)-based differential synthetic aperture radar (SAR) tomography (D-TomoSAR) technique presents an attractive approach for urban risk monitoring. With its sufficiently long spatial and temporal baselines, it offers elevation and velocity resolution beyond the dimensions of range and azimuth, enabling four-dimensional (4D) SAR imaging. In the case of P-band UAV-SAR, a long spatial-temporal baseline is necessary to achieve high enough elevation-velocity dimensional resolution. Although P-band UAV-SAR maintains temporal coherence, it still faces two issues due to the extended spatial baseline, i.e., low spatial coherence and high sidelobes. To tackle these problems, we introduce a multi-master (MM) D-TomoSAR approach, contributing three main points. Firstly, the traditional D-TomoSAR signal model is extended to a MM one, which improves the average coherence coefficient and the number of baselines (NOB) as well as suppresses sidelobes. Secondly, a baseline distribution optimization processing is proposed to equalize the spatial–temporal baseline distribution, achieve more uniform spectrum samplings, and reduce sidelobes. Thirdly, a clustering-based outlier elimination method is employed to ensure 4D imaging quality. The proposed method is effectively validated through computer simulation and P-band UAV-SAR experiment.
KW - P-band
KW - differential SAR tomography (D-TomoSAR)
KW - multi-master
KW - sidelobe suppression
KW - unmanned aerial vehicle (UAV)
UR - http://www.scopus.com/inward/record.url?scp=85159282719&partnerID=8YFLogxK
U2 - 10.3390/rs15092459
DO - 10.3390/rs15092459
M3 - Article
AN - SCOPUS:85159282719
SN - 2072-4292
VL - 15
JO - Remote Sensing
JF - Remote Sensing
IS - 9
M1 - 2459
ER -