Are there hidden structures below the pyramids of Giza?

In 2022, Filippo Biondi and Corrado Malanga published a method that processes a single satellite radar image to reveal subsurface structure. They applied it to the Great Pyramid of Giza and reported imaging internal chambers and features deep below the plateau. A 2025 press conference extended the claim to large structures hundreds of metres underground, and the story went viral.

Does the published method actually show what the viral claim says it shows?

I could not reproduce evidence that the published method detects chambers or deep structures beneath the Great Pyramid.

The baseline geometry of a single satellite pass is too small to resolve features at the depth of the known internal chambers, let alone hundreds of metres down. My empirical tests produced near-identical depth profiles for the Great Pyramid, nearby desert, the Nile, downtown Cairo, and other unrelated locations. The method returns similar-looking "structures" wherever you point it. They are more plausibly reconstruction artifacts than buried architecture.

Millions of people saw the claims but nobody checked the paper.

Last year, an Italian engineer named Filippo Biondi went viral by claiming he had discovered deep underground structures beneath the Giza pyramids. In January 2026, he went on Joe Rogan and explained his findings in detail. According to his research, under the Great Pyramid there are shafts extending 600m down and structures at over a kilometer of depth. He showed colorful images, referenced his 2022 peer-reviewed paper, and mentioned the Italian Space Agency.

He also pointed to two validations. First, he said the method correctly detected the Grand Gallery, Queen's Chamber, and King's Chamber inside the Great Pyramid. Second, he said it picked up the Gran Sasso physics laboratory, about 1.4 kilometers inside a mountain. If the method gets the known targets right, the unknown deep structures are supposed to look much more credible.

That is an extraordinary claim. If true, it would rewrite a lot more than pyramid archaeology.

On the show he also encouraged independent verification, since the experiments can be run with openly available data sources. I'm not a radar scientist, I didn't know what SAR was until recently, and I have no university affiliation. But I read the paper, I have a computer, and I got curious enough to try reproducing it.

Can this method actually see a chamber 43 meters inside the pyramid?

The first thing I did was the low hanging fruit: checking whether the method can actually see the chambers inside the Great Pyramid.

The method, as described in the paper, is supposed to work from a single satellite radar image. You split that image into Doppler sub-apertures, treat those as slightly different viewing angles, and use them to reconstruct depth. The pitch is basically: one image in, underground tomography out.

That sounds amazing. It also creates a very simple question:

Are those angle differences actually large enough to distinguish different depths?

I pulled the orbital parameters from real X-band radar data over Giza and ran the geometry. The answer I got was about 285 meters of elevation resolution. That means anything within a 285-meter slice gets blurred together into one unresolved lump.

The King's Chamber, one of Biondi's main validation targets, is about 43 meters above the pyramid's base. The Queen's Chamber is about 21 meters. Both are far smaller than a single resolution cell. In plain English, the published single-pass method is not able to separate those chambers from the surrounding structure.

That limitation comes from orbital geometry. The satellite is simply too far away and the angle differences are too small. No amount of parameter tuning changes that.

But maybe I'm wrong. Let's test it.

Maybe my geometry argument was too simplified. Maybe Biondi knows something about the processing that I was missing. So I tested it empirically.

I took two patches from the same Giza radar scene. One was centered on the Great Pyramid and the other was centered on nearby empty desert. Then I ran the same family of processing on both.

If the method is actually detecting underground structure, the pyramid should behave differently from the desert. The pyramid contains known internal chambers, while the desert does not.

That is not what happened.

I ran 240 experiments, systematically sweeping across sub-aperture count, bandwidth ratio, filter choice, and depth range.

Result: zero of 240 experiments distinguished the pyramid from the desert. In every experiment, I measured how strongly the method responded in the depth range where the known chambers sit. On average, the empty desert produced a slightly stronger response than the Great Pyramid.

That is not a subtle result.

If empty sand can match or beat the Great Pyramid, the method is not giving you a clean underground detection.

20 locations. All identical.

I still wasn't satisfied though. Maybe something about the desert specifically was confusing the method.

As a further check, I ran the same processing across 20 different locations in the same radar scene: the Great Pyramid, the Pyramid of Khafre, the Sphinx, the Step Pyramid at Saqqara, downtown Cairo, the Nile River, farmland, and several random spots with nothing notable underground.

The resulting depth profiles were all strikingly similar. The average correlation with the Great Pyramid profile was 0.975.

According to this method, the Nile River has the same underground structures as the Great Pyramid.

Why the method sees "structures" everywhere

The best way to think about this is: the method is trying to build a huge depth story from very little real depth information.

When you do that, the reconstruction has to fill in the blanks. And when the blanks are large enough, the math starts producing convincing-looking patterns that aren't real.

That is what my simulation showed.

In that simulation, I manually planted a few known shallow pyramid features into a toy model, like the Queen's Chamber, King's Chamber, Grand Gallery, and the pyramid's base. Then I ran the same kind of tomographic reconstruction on top of them. I did this to test a simple question: if the real structure is shallow, can the reconstruction itself manufacture fake deep structure lower down?

The answer was yes.

Using a sparse setup equivalent to the six-image configuration listed in the paper, the reconstruction produced strong structured-looking depth patterns far below the shallow features I had planted into the model. When I switched to a much denser 200-image setup, those deep artifact patterns started to disappear, and the simulation was left mostly showing the shallow planted features. In other words, the dramatic deep stuff faded when I added more real information. That is what you expect from artifacts, not buried architecture.

This matters because Biondi's public presentation relies heavily on visually persuasive tomographic images. But sparse reconstructions are perfectly capable of generating visually persuasive nonsense.

If you already expect shafts, chambers, spirals, or giant underground structures, it becomes very easy to read artifact patterns as discoveries.

The Gran Sasso "validation" — finding what you're looking for

This also explains the Gran Sasso "validation."

The laboratory sits 1,400 meters inside a mountain. Biondi processed the radar data, looked at 1,400 meters depth, and found a bright feature. Validation confirmed, right?

Not really.

The whole problem is that this kind of reconstruction can generate bright, structured-looking responses across the entire depth axis. If you already know there is a laboratory at 1,400 meters and then go looking at exactly 1,400 meters, it is very easy to mistake one more reconstruction artifact for a successful detection.

This is the same pattern I saw in my Giza tests. The method produces structure everywhere, not just where real targets exist. I would expect similar-looking 'detections' at comparable depths in neighboring mountains with no laboratory at all.

The method seems perfectly capable of producing meaningful-looking structure almost anywhere you ask it to look.

One image or six?

Up to this point I had been testing the paper the way the paper describes itself: as a single-pass method.

One radar image goes in. A depth reconstruction comes out.

But then I noticed something odd.

The published method is framed as single-pass. Yet the paper also lists six acquisitions from six different dates, and the acknowledgments thank the developer of SARPROZ, which is a multi-temporal SAR processing tool. That raises a very basic question:

Was this really single-pass at all?

Because those are completely different things.

Single-pass Doppler sub-aperture processing creates tiny virtual baselines from one image. Multi-pass interferometric SAR uses real orbital baselines from different passes on different dates. One gives you very little geometric leverage. The other can give you much more.

That distinction becomes even more important because on Rogan Biondi said they had run more than 200 scans and got uniform results. If that means 200 truly independent single-pass runs, then my geometry objection applies to each one. If it means a large multi-pass stack, then we are no longer talking about the same method the paper advertises.

If the real workflow was multi-pass, then the paper's central single-pass framing is at best incomplete and at worst misleading.

What he might have actually found

So what's actually going on?

I don't think this is fraud, and I don't think it's total nonsense either.

My best guess is that Biondi's apparent chamber detections came from a different workflow than the one the paper describes, most likely some form of multi-pass processing with real orbital baselines, which is an established technique. Those detections may have validated the method in his eyes. From there, the sidelobe artifacts at greater depths may have looked like new discoveries, and nobody checked whether they were real.

But that explanation doesn't rescue the paper. If the real results came from multi-pass processing, then the published single-pass method gets none of the credit. And the deep structures remain far more plausibly artifacts than genuine underground architecture.

The published single-pass method does not justify the claims being made for it.

Check my work

Before publishing this, I emailed Prof. Biondi. He has publicly encouraged independent replication, and this is exactly that: an independent attempt to reproduce the published method.

All the code is open source, all the data is freely available. Anyone who wants to check the numbers can do it.

If I'm wrong please let me know. I really wanted to believe there were underground structures and went into this process looking for them. Unfortunately I ended up finding out they're just artifacts.

Coming later.

Primary target paper

• Biondi, F.; Malanga, C. (2022). "Synthetic Aperture Radar Doppler Tomography Reveals Details of Undiscovered High-Resolution Internal Structure of the Great Pyramid of Giza." Remote Sensing 14(20), 5231. https://doi.org/10.3390/rs14205231

Companion / related Biondi work

• Biondi, F. (2022). "Scanning Inside Volcanoes with Synthetic Aperture Radar Echography Tomographic Doppler Imaging." Remote Sensing 14, 3828. https://doi.org/10.3390/rs14153828
• Biondi, F.; Addabbo, P.; Clemente, C.; Orlando, D. (2019). "Measurements of Surface River Doppler Velocities..." Remote Sensing 11, 766. https://doi.org/10.3390/rs11070766
• Biondi, F.; Malanga, C.; Mei, A. Press conference, Castel San Pietro Terme, March 15-16, 2025. Subsurface "city" claims; not peer-reviewed.

SAR tomography foundations

• Reigber, A.; Moreira, A. (2000). "First Demonstration of Airborne SAR Tomography Using Multibaseline L-Band Data." IEEE TGRS 38(5), 2142-2152. https://doi.org/10.1109/36.868873
• Fornaro, G.; Lombardini, F.; Serafino, F. (2005). "Three-Dimensional Multipass SAR Focusing." IEEE TGRS 43(4), 702-714. https://doi.org/10.1109/TGRS.2005.843567
• Lombardini, F. (2005). "Differential Tomography: A New Framework for SAR Interferometry." IEEE TGRS 43(1), 37-44. https://doi.org/10.1109/TGRS.2004.838371
• Zhu, X.X.; Bamler, R. (2010). "Tomographic SAR Inversion by L1-Norm Regularization." IEEE TGRS 48(10), 3839-3846. https://doi.org/10.1109/TGRS.2010.2048117
• Zhu, X.X.; Bamler, R. (2010). "Very High Resolution Spaceborne SAR Tomography in Urban Environment." IEEE TGRS 48(10), 4296-4308.
• Fornaro, G.; Pauciullo, A. (2009). "LMMSE 3-D SAR Focusing." IEEE TGRS 47(1), 214-223.

SAR penetration physics

• McCauley et al. (1982). Science 218(4576), 1004-1020. https://doi.org/10.1126/science.218.4576.1004
• Schaber, G.G. et al. (1986). IEEE TGRS GE-24(4), 603-623. https://doi.org/10.1109/TGRS.1986.289677
• Schaber, G.G.; Breed, C.S. (1999). Remote Sensing of Environment 67, 318-332.

Ionospheric / split-spectrum

• Gomba, G. et al. "Toward Operational Compensation of Ionospheric Effects in SAR Interferograms: The Split-Spectrum Method." PDF in project knowledge.

Independent Giza subsurface ground truth

• Morishima, K. et al. (2017). "Discovery of a Big Void in Khufu's Pyramid by Observation of Cosmic-Ray Muons." Nature 552, 386-390. https://doi.org/10.1038/nature24647
• Procureur, S. et al. (2023). Nature Communications 14, 1144. https://doi.org/10.1038/s41467-023-36351-0
• Cardarelli, E. et al. (2025). "Confirmation of the Scanpyramids north face corridor in the Great Pyramid of Giza using multi-modal image fusion..." Scientific Reports 15, 9275. https://doi.org/10.1038/s41598-025-91115-8
• Elkarmoty, M. et al. (2023). "Localization and shape determination of a hidden corridor in the Great Pyramid..." NDT & E International 139, 102809. https://doi.org/10.1016/j.ndteint.2023.102809
• Cardarelli, E. et al. (2025). "Modified ERT cavity detection..." Scientific Reports 15, 41187. https://doi.org/10.1038/s41598-025-29081-4

• Paper on Zenodo
• Reproduction code on GitHub