Source Code for GUI

Hosted here: https://github.com/goretkin/soundcard-radar

"Slashdot" effect

More SAR

SAR'd the following scene:

which generates the following image:

which shows the wall edge at ~20 feet. The image is reflected from the actual scene because we reversed the direction we swept the sensor without changing it in code.

Synthetic Aperture Radar!

Adam, who's on the team with me, generated the following images with the code that Greg Charvat provided.

It looks pretty plausible! Here is the scene:

Adam and I acquired the SAR data last night(/morning) right outside 32-123. The two strong objects nearby are the door to 32-123 and the polygonal column. The reflections at 150 feet appear to be the cylindrical column on the right garnished with metal chairs. The center reflections at around 0-60 feet are likely reflections from the floor.

It was possibly one of the worst nights we could have tried to collect the data; some people were playing laser tag but they kept to the Gates side.

Worst. Sonogram. Ever

We took a series of range profiles along a linear axis at two inch increments in order to try to do Synthetic Aperture Radar (SAR)


 I thought I'd try a naive, intuitive algorithm for reconstructing the SAR scene

...

Cleaner Ranging and Multiple Targets

I got my friend Rachel to be an additional target. You should be able to make out the both of us in the range vs. time plot. We cross paths twice. Here is the original screen cap.

I decreased the time constant in the complementary IIR filter that subtracts static objects from the range measurements. That means that static objects decay more quickly. This seems to have helped a lot in the clutter. I also try to compensate for free-space path loss (signals which propagate further decay). Greg Charvat suggests using the model that the signal decay is proportional to (R^3/2) where R is the distance traveled. Since I'm plotting log of intensity of the frequency components over time, I just add 3/2(log R).  Any scaling difference in R manifests itself as a shift. Since I am streaming the spectrogram in real-time, I haven't yet done anything to try to maximize the contrast in the spectrogram. That would probably make the trajectories appear much more clearly.

Radar Ranging

I think I got some pretty okay ranging results. You've got to use your imagination to make it out. I resorted again to taking a screen capture of my webcam and the radar data...

The embedded videos are downsampled. Here's the original screen cap.
Notice that, as I scooter away, there is an increasing frequency component. As I scooter back there is a component that is decreasing in frequency. See if you can discern the difference in rising and falling slope. I'm going faster on the return than I am during the departure.

The "Spectrum" graph on the left is a low-pass filtered version of the ranging signal. This is subtracted from the current ranging information so that in the spectrogram only moving reflections are shown. Even with this, there is a lot of "clutter" in the radar image. Also, I'd like to improve the dynamic range. The higher frequency components in the ranging data are a result of reflections from farther away. These signals are attenuated due to free-space path loss. Confer, for example, with when I am right in front of the antennas and there is a significant red mass on the spectrogram.