Take a look at the picture above. Without the labels, would you be able to figure out what you are looking at? Do you think this image contains a lot of high-quality information?
Without a background in radar imagery analysis, the answer will likely be a resounding “no” to both questions.
Think about how differently an Egyptologist and a tourist look at hieroglyphics. Intuition can only go so far in terms of comprehension. Training accounts for the rest.
It may be surprising to learn the image above captures a train in motion. It’s probably even more surprising to learn you can also calculate how fast the train is moving.
How is that possible?
It may be easier to begin by explaining what this picture is not. It’s not an optical image, taken by a powerful camera attached to a satellite, like the kind you see on Google Earth.
Instead, a different type of sensor called synthetic aperture radar (SAR) was used to form the image of the train above. Unlike an optical sensor, SAR works day or night, in any weather conditions.
The following imagery shows an optical versus a SAR image of the same place.

With SAR, a radar antenna is fixed to a satellite that emits a beam. The beam interacts with the earth’s surface and then returns to the sensor. This same process is repeated over and over.
The returned energy contains information that allows for the measurement of presence, direction, speed and distance.
This idea isn’t as foreign as it might sound at first.
Bats, dolphins and whales use a similar technique called echolocation for the purposes of hunting prey and communicating. These animals emit radio frequency pulses that relay information about objects ahead. The difference in the frequencies between the sent and received chirps indicates whether an object is static, or moving closer or further away.

This technique allows animals to navigate and survive under low visibility conditions caused by darkness or limited eyesight.
We humans rely more on visual input than acoustics. But it’s possible to imagine how the sound of an echo could be used to better understand your surroundings.
This is the general concept of how a radar sensor works, but there’s an important caveat:
When a moving object is present during the formation of a SAR image, that object appears in the image as displaced from its true position.
What does this mean?
Look again at the SAR image at the top of this page. The train appears as a white, diagonal line that is parallel to the train tracks.
Of course, that’s not real. The train is, in fact, moving on the tracks. This shift is a quirk of standard SAR processing methods, which assume the objects in view are stationary.
When that assumption is incorrect, the moving object can be displaced from its true location. In SAR imagery, trains and boats in motion can appear “off-track,” as a result.
The next SAR image is another example of the displacement of moving objects. It captures five boats in the Strait of Malacca. The true location for each boat is revealed by the wake.

Strait of Malacca, Imagery from ICEYE, 2020
This phenomenon is well-understood by the SAR community. It also serves a purpose. You can estimate the moving object’s actual speed and direction based on the amount and direction of displacement with respect to the SAR-sensor’s position in orbit.
This trade-off is one of the defining features of SAR.
A SAR image doesn’t always conform to the Google Earth-type satellite imagery we are used to. It is not natively easy to interpret using the visual lens we’re accustomed to. Its value lies elsewhere, in the multi-dimensional information (e.g. speed, direction, distance, presence) that can be unlocked if SAR analysis is done correctly.
Given its strengths, the applications for SAR are vast, though it could be said its adoption in the commercial sector is still in the early stages.
That won’t be the case for long, however. Recent developments in the satellite industry have laid the foundation for exponential growth.
Want to learn more about how SAR works? Watch this video by Ursa Space’s Chief Technology Daniela Moody.