Python Script for the MIT Radar Short Course

I have been following Gregory L. Charvat's work on small inexpensive radars for a while now, and was quite happy to see that the course material for one of his radars were made available online at the MIT Open Courseware website.

I wanted to make sure I can process the data first. The scripts that came with the course material are written in Matlab, and I thought it would be a good learning exercise to try to convert them into Python. Greg and I wanted to make the Python module available for people who may not have access to Matlab. Below are some results and their comparison with the results provided in the course material.

The first lab is about generating a Doppler Time plot. On the left you see the result from the lab pdf, and on the right you see my results. The Matlab image may appear on top if your screen resolution is not wide enough.

matlab-lab1 python-lab1

The second lab is on observing Doppler history of moving targets. There seems to be a difference in the magnitude of the signal, and it may be due to incorrect scaling of amplitude with range. I will check the scripts later on and update the results and script if I can come up with a better result. Again the original result is on the left, while mine is on the right below.

matlab-lab2 python-lab2

The third lab is about generating a synthetic aperture radar image using the data collected on a straight trajectory. Again there seems to be a slight difference in the amplitude of the signal, but in general the results look very similar. The minor difference here might just be due to slightly different color scales or the scaling of amplitude with range again. The original result is on the left, and my result is on the right.

matlab-lab3 python-lab3

The Matlab scripts along with the data I used can be downloaded from the MIT Open Courseware web page, which is listed at the references below. The Python module is available also available below, shares the same license as Greg's original code, so please cite him appropriately for this work.

Please note that the Stolt interpolation in SBAND_RMA_IFP function takes quite some time. I used a progress timer available from the basic.py module of ADORE-DORIS project. The link to that is also available in references. I disabled this module from the code below, and you don't need to download basic.py if you are patient enough ;)

References