Unlocking the Power of Single-Antenna-Single-Pass SAR Interferometry for High-Resolution Earth Science Radar Imaging

Introduction

Synthetic Aperture Radar (SAR) has revolutionised remote sensing applications by providing high resolution images of the Earth’s surface in all weather conditions. SAR interferometry (InSAR) is a technique that uses two SAR images of the same area to measure surface deformation. However, traditional InSAR algorithms require two antennas or passes to obtain the necessary phase information, limiting the temporal and spatial resolution of the technique. Single-Antenna-Single-Pass SAR Interferometry (SASI) is a new technique that overcomes this limitation by extracting the necessary phase information from a single SAR image acquired with a single antenna. In this article, we explore the principles of SASI and its potential applications in earth science radar imaging.

The principles of SASI

SASI is based on the fact that the phase of a SAR image is modulated by the topography of the ground and the position of the sensor. This modulation is referred to as the SAR phase history. By exploiting the relationship between the SAR phase history and the topography of the ground surface, SASI is able to extract the required phase information from a single SAR image. The key to this technique is the use of a Digital Elevation Model (DEM), which provides information about the topography of the ground surface. By comparing the SAR phase history with the DEM, SASI is able to determine the phase contribution of the topography, which can be removed from the SAR phase history. The remaining phase information is then used to generate interferograms which can be used to measure ground deformation.

SASI has several advantages over conventional InSAR techniques. First, it requires only a single SAR image and antenna, which reduces data acquisition costs and increases temporal resolution. Second, it is not affected by atmospheric disturbances that can cause phase errors in traditional InSAR algorithms. Third, it can be used to generate interferograms in areas with complex topography where traditional InSAR algorithms may fail.

Applications of SASI in earth science radar imaging

SASI has several potential applications in Earth science radar imaging. One of the most promising is the monitoring of volcanic activity. Volcanic deformation is an important indicator of volcanic activity, and traditional InSAR techniques have been used to monitor volcanic deformation for decades. However, traditional InSAR algorithms require two passes, which limits their temporal resolution. SASI can overcome this limitation and provide high resolution deformation maps of volcanoes in near real time.

Another potential application of SASI is the monitoring of landslides. Landslides are a major hazard in many parts of the world, and traditional InSAR techniques have been used for decades to monitor landslide activity, but traditional InSAR algorithms require two passes, which can limit their temporal resolution and make them less effective for monitoring rapidly evolving landslides. SASI can provide high-resolution deformation maps of landslides in near real time, making it a valuable tool for hazard mitigation and disaster response.
SASI can also be used to monitor subsidence in urban areas. Subsidence is a common problem in many cities around the world and can be caused by a variety of factors, including groundwater extraction, soil compaction and underground mining. Traditional InSAR techniques have been used to monitor subsidence for many years, but are limited by their temporal resolution and sensitivity to atmospheric disturbances. SASI can provide high resolution subsidence maps with high temporal resolution, making it a valuable tool for urban planning and infrastructure management.

Challenges and future directions

Despite its many advantages, SASI still faces several challenges that need to be addressed before it can reach its full potential. One of the main challenges is the accuracy of the DEM used in the technique. Any errors or inaccuracies in the DEM can lead to errors in the phase estimation, which can affect the accuracy of the deformation measurements. Another challenge is the sensitivity of the technique to changes in the topography of the ground surface. Any change in topography, such as vegetation growth, can affect the accuracy of the technique.
It is expected that SASI will continue to evolve and improve in the future. One potential direction for future research is the development of new algorithms to improve the accuracy of the technique. For example, machine learning techniques could be used to improve the accuracy of the DEM or to develop new algorithms for phase estimation. Another direction for future research is the integration of SASI with other remote sensing techniques, such as LiDAR or optical imaging, to provide a more comprehensive view of the Earth’s surface.

In summary, SASI is a powerful new technique for high-resolution Earth science radar imaging. By extracting the necessary phase information from a single SAR image, SASI overcomes many of the limitations of traditional InSAR techniques and has the potential to revolutionise the way we monitor and understand the Earth’s surface. While there are still challenges to overcome, the future of SASI looks bright and we can expect to see continued advances and improvements in the technique over the coming years.