A Brief Introduction to Ice-Penetrating Radar | Hacker News Reader

A Brief Introduction to Ice-Penetrating Radar

lindzey.github.io

79 pointsDalekBaldwin16 comments

Really nice writeup! I wish more graduate students would blog about their research in this way. Could be a great way to educate the public and convey the importance of government research funding.

I wonder how big the reflection coefficient is for the air/ice interface. It seems like it would be huge. So maybe ground based techniques offer better coupling at the cost of not being able to survey as much area?

We record on two channels, "high gain" and "low gain", separated by ~50dB. I showed the high gain products in this post, and the surface absolutely does saturate the detectors. The system was designed so that near-surface returns don't saturate the low gain channel.

We transmit 8kW, and the air/ice surface reflection coefficient is ~0.08 (~-11dB). Flying at ~600m above the surface, spreading loss actually contributes more to signal attenuation (1/(2*h)^2 ~= -62dB).

Our instrument is optimized for seeing through the entire ice sheet, mapping deep layers and the bed. Other (also airborne) instruments operate at higher frequencies, trading higher resolution for less penetration. I'm not super familiar with groups using ground-based ice-penetrating radar, but one big tradeoff is $$$. The airplane is hugely expensive to operate, whereas ground-based just needs a snowmobile.

On a related note: My father is a geophysicist and he is using ground penetrating radard for archeo prospection. It's really amazing. The software can reconstruct entire ancient cities from the GPR signal.

I had the opportunity to collect and work with similar data during grad school. I love the fact that these guys use a DC-3; very cool. We used a sled.

Thats really pretty amazing. Filtering out the 'echos' would clearly make the data more useful, but I can see how thats almost impossible without very clever engineering

There's some work in SAR stuff on that sort of thing. One sketch of an idea would be to iteratively estimate the measurement including multi-path from what you think the surfaces look like and then remove the "surfaces" that are explained by echos off of single surfaces. The goal would be to get images that explain the measurements you take using the fewest number of surfaces.

This is trickier than normal imaging, because if you ignore the multiple reflections you're basically just inverting a matrix (a fourier transform in the case of single line imaging). With multipath the measurement becomes nonlinear in your scene and inversion isn't as trivial.

Another alternative is to sweep the radar so you get multiple revisits from different times and angles. Stacking the revisits at a location will suppress the multipath since, in theory, the multipath components depend more strongly on grazing and aspect angle than the "real" components.

Absolutely! I only included our lowest-level data products in this post. We don't sweep the radar side-to-side, but since it's on a moving platform, we see the same thing from multiple angles. In the data I showed, there has been some very limited stacking applied, mostly just to improve the signal-to-noise ratio. The next level of processing would be focusing/migration (depending on whether you're in the radar or seismic world) - it reasons about possible incident angle and collapses the hyperbolas to a single point.

Unfortunately, this only improves the resolution along the flight track; features parallel to the flight path and offset to the side are the hardest to filter out.

Using our sensor geometry, there's an ambiguity from where off to the side the energy was returned from. So, the solution would wind up being non-unique whatever you do.

There has been some fun work along the lines you describe that uses maps of the surface shape (generated from camera imagery or scanning laser data) to discriminate which apparently-subsurface echoes are most likely due to the surface topography. So far as I know, this hasn't been automated - it's more an aid to human interpretation (we have an army of undergrads that "picks" the most likely bed location).

I'm not familiar with SAR, but it seems like they could use more than just 2 antennas to produce a more directional receive array. I work with HF radars (2-30 MHz) and this is basically what we do. There is a lot of clever engineering out there - that one doesn't need to be too clever to apply.

Yes - this idea has definitely taken over my imagination. A different research group (https://www.cresis.ku.edu/) has been working on this, but the processing techniques are still evolving.

Do you have papers describing y'all's processing? I'd love to learn more!

I think "phased array radar" is the relevant search term.

I do have papers. I recently wrote a paper where we used backscatter from container ships to calibrate our radars. I'll try to email it to you, but here it is:

http://euler.msi.ucsb.edu/papers/2014_emery_apm_from_soo.pdf

It has some of the basic processing techniques.

Can't they do some frequency hopping or encode some sort of timestamp in the radar signal to identify when they sent out the wave they're receiving?

This is a pulsed system - we send out 1us wide chirped signals, then listen for their returns before sending out the next signal. So - we know how far away a return is, but the tricky bit is knowing which direction it came from, since our beam pattern is so wide.

We do use a chirped signal in order to improve vertical resolution - convolving the outgoing pulse with the returned trace gives us the equivalent resolution of a ~80ns pulse, but with more power.

An acquaintance of mine is prepping for a cruise to do some sea-ice measurements. They'll be on the RV Sekuliak though, not an airplane.

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