Abstract
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.
Highlights
In comparison to spaceborne synthetic aperture radar (SAR), ground-based SAR (GBSAR) has an inherent flexibility of allowing adjustable temporal resolution in data acquisition
This paper describes the main endeavors addressing random-access memory (RAM) management, real-time capability, and the reliability of processing consecutive GBSAR data with high temporal resolution and large data volumes
Atmospheric phase screen (APS) was corrected by regressing a linear range-dependent model with 10% of the selected temporally-coherent pixels
Summary
In comparison to spaceborne synthetic aperture radar (SAR), ground-based SAR (GBSAR) has an inherent flexibility of allowing adjustable temporal resolution in data acquisition. Depending on the rate of change in any particular case study, or the practical environment for instrument deployment, GBSAR data acquisition can be performed in either continuous or discontinuous mode [1,2,3,4]. The continuous mode employs a zero-baseline geometry for all acquisitions, avoiding influences of hardware related technical issues and leading to better performance in terms of the density, precision, and reliability of deformation measurements [5,6]. This study focuses only on continuous GBSAR deformation monitoring. Consecutive acquisitions with a high temporal resolution (up to several seconds) enable time series analysis of fast-changing scenarios that can provide insight into mechanisms and triggering factors of hazardous events, or even act as the basis for early warning systems. In practice, the processing of continuous GBSAR data has the following characteristics:
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