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Open AccessArticle

A New Processing Chain for Real-Time Ground-Based SAR (RT-GBSAR) Deformation Monitoring

1
School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
2
Ocean Geomatics Center, The First Institute of Oceanography, State Oceanic Administration in China, Qingdao 266061, China
3
School of Land Science and Technology, China Univ. of Geosciences, Xueyuan Rd. 29, Beijing 100083, China
4
Hunan Key Laboratory of Coal Resources Clean-utilization and Mine Environment Protection, Hunan University of Science and Technology, Xiangtan Hunan, 411201, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(20), 2437; https://doi.org/10.3390/rs11202437
Received: 12 September 2019 / Revised: 15 October 2019 / Accepted: 16 October 2019 / Published: 20 October 2019
Due to the high temporal resolution (e.g., 10 s) required, and large data volumes (e.g., 360 images per hour) that result, there remain significant issues in processing continuous ground-based synthetic aperture radar (GBSAR) data. This includes the delay in creating displacement maps, the cost of computational memory, and the loss of temporal evolution in the simultaneous processing of all data together. In this paper, a new processing chain for real-time GBSAR (RT-GBSAR) is proposed on the basis of the interferometric SAR small baseline subset concept, whereby GBSAR images are processed unit by unit. The outstanding issues have been resolved by the proposed RT-GBSAR chain with three notable features: (i) low requirement of computational memory; (ii) insights into the temporal evolution of surface movements through temporarily-coherent pixels; and (iii) real-time capability of processing a theoretically infinite number of images. The feasibility of the proposed RT-GBSAR chain is demonstrated through its application to both a fast-changing sand dune and a coastal cliff with submillimeter precision. View Full-Text
Keywords: ground-based synthetic aperture radar; interferometry; time series analysis; real-time; deformation monitoring; small baseline subset algorithm ground-based synthetic aperture radar; interferometry; time series analysis; real-time; deformation monitoring; small baseline subset algorithm
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Wang, Z.; Li, Z.; Liu, Y.; Peng, J.; Long, S.; Mills, J. A New Processing Chain for Real-Time Ground-Based SAR (RT-GBSAR) Deformation Monitoring. Remote Sens. 2019, 11, 2437.

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