SAR 201: An Introduction to Synthetic Aperture Radar, Part 2

Daniel Hogan
The DownLinQ
Published in
8 min readFeb 13, 2020

By Daniel Hogan (In-Q-Tel CosmiQ Works) and Jason Brown (Capella Space) with the CosmiQ Works and Capella teams.

Preface: SpaceNet LLC is a nonprofit organization dedicated to accelerating open source, artificial intelligence applied research for geospatial applications, specifically foundational mapping (i.e. building footprint & road network detection). SpaceNet is run in collaboration with CosmiQ Works, Maxar Technologies, Intel AI, Amazon Web Services (AWS), Capella Space, Topcoder, and IEEE GRSS.

Synthetic aperture radar (SAR) provides all-weather ground imaging, but SAR images are quite different from optical images. This post gives an overview of data analysis methods used with SAR and what can be learned from SAR imagery. This concludes a discussion begun in a previous post, which looked at how SAR images are produced. SAR data is featured in the soon-to-begin SpaceNet 6 Challenge.

SAR Data

As introduced in the previous post, SAR is a coherent imaging method. This enables techniques like interferometry, covered in the next section, to be achieved. Since SAR is a coherent imaging method the returns have two components, the intensity and the phase.

Figure 1. Intensity (left) and phase (right) components of SAR data (Courtesy: Capella)

The intensity component of SAR data is the part that looks like an image after SAR image formation processing has occurred. The radio waves in the SAR beam are aligned in space and time (coherent) upon transmission, or in other words they are “in phase.” The phase component of SAR data measures how much the radio waves have shifted “out of phase” after they interact with the scatterers on the surface. These phase components are useful, because phase differences between different channels or different collects can reveal information about the geometry and composition of the scene.

Single Look Complex

SAR data can be delivered as Single Look Complex (SLC) data where the intensity and phase components are represented as complex numbers for each pixel. Intensity and phase values can be subsequently computed from the complex numbers. Intensity and phase can be viewed as images, as seen in Figure 1, though only the intensity component is recognizable as an image. Additionally, SLC data is in the radar-image…

Daniel Hogan
The DownLinQ

Daniel Hogan, PhD, is a data scientist at CosmiQ Works, an IQT Lab.