> Recently small FPV drone prices have dropped a lot. Small 5 and 7 inch propeller quadcopters can be bought for about 100 EUR from China (not including battery and RC controller). Despite their small size they are able to lift about 1 kg or even heavier payload which is plenty for a small radar.
The price dropped because China is selling these things by the truckload to both sides in Ukraine. China is benefitting from the economics of scale, Russia and Ukraine are each burning through on the order of 100,000 of these things each month and most components are sourced from China
I wonder what the % breakdown is for domestic vs imported drones for Ukraine?
I read recently that Ukraine was producing a lot of drones and ramping up production too, as well as using fibre-optic controlled drones to overcome electronic warfare/jamming.
You won't get any reliable numbers during wartime. I heard Ukrainian government recently mention they ordered a million.
Hundreds of small companies (around 10 employees each) in Ukraine are making and assembling drone's right now (according to journalists who filmed them in Ukraine last month). I counted at least two dozen companies in the Netherlands, probably a few hundred all over Europe. Besides the frame that holds the 4 or six rotors together all other parts are off the shelf, mostly ordered from Shenzen. You can CNC mill a carbon fiber or aluminum frame from a single plate on an x-y flatbed cnc.
I researched all this last night because I need $20K-$200k investment right now to start my own startup making unjammable autonomous kamikaze drones with 20K payload on top of 20km optical fiber spools unreeling. I think it is possible to make them lighter without fibers if you put a few thousand microprocessors in with a wafer scale integration for $500.
Of course you could just make cheap drones that kill every warm body in sight[4] indiscriminately. To disable a tank you need these fiber tethered drones with bigger payloads[3][5][6]. You cab see two fiber strands still in the air in a few frames of the video.
What you need is a Paul MacCready style development cycle for drones in the field. You need to be able to make 10 crashes per hour, fix the drone by replacing with off-the shelf components and try again. The programming should be live-coding like Squeak Smalltalk, no recompiling, just fix and run while you are using the software to edit itself [1] as Dan did in 1976[2] on this 5.88 mhz computer. We still code like this today but most programmers and managers ignore this in favor of terminals and simulated punch cards. Remember that it took humans 200.000 years to invent written language or agriculture, we just are not that smart.
hm... and why are the drones carrying the whole spool of the fiber instead of leaving the spool on the ground and unraveling it from there without the extra weight on the drone?
unraveling a stationairy ground based spool first tangles quickly if you lift two loops instead of one. Even if you had a dispencer hole you still snag loops under the dispenser that might get knots and snag the drone.
Second, you would now have to drag the whole fiber from the drone down to the ground, overcoming the kilometers resistance dragging all the cable over the ground and on top of all that extra force you also have to put tension on the spool at the start to unwind it.
If you unwind the spool hanging under the drone by a rotating shaft through the spool, you do not have any tension on the fiber (but for a few grams of its weight if you unspool to slowly) and the weight of the fiber in the air even helps unspool the fiber (although you want to prevent that by speeding up the unwinding)
this may sound like a stupid question... but why not use google maps, ground images, and run a basic cnn to obtain positioning? That wouldn't require you to have it dragging/ carrying a bunch of fragile nanowire... which seems... not right?
The fiber is to (1) prevent jamming the radio control of the motors and ammunition by an operator and (2) receive a higher resolution higher frame per second multiple camera stream and (3) to ensure the operator can't be traced and targeted by triangulating the wifi antenna of the operator and (4) to allow networking by plugging in the stationairy start of the fiber into a switch connected to full internet network with thousands of kilometers of fiber between the operator and the drone so (5) the operator can be different from the drone launcher and (6) have the drone be operated by a supercomputer or datacenter with more and more accurate video frame interpretation.
Its a difference of dragging a line and just laying it out as you go. A lot less resistance to just pay out the spool so there is no tension in the wire.
As a DIYer myself I am awed by how much Henrik has managed to flesh out in terms of complexity: signal processing, hardware, GPU acceleration, and algorithmic optimizations. I wish the HN community had some award for such incredible feats.
This is absolutely amazing work but I would not call him a hobbyist.
Again not diminishing the work but adjusting the expectations, this output is not from a curious guy in a shed. He is a trained Electrical Engineer working as a Senior Consultant/Scientist in RF design for a Finnish Engineering Consultancy.
This guy clearly has a breadth and depth of knowledge from his professional career which he brings with him into his out-of-office projects.
SAR = Synthetic Aperture Radar, where the radar flies along a straight line and the apparent rotation of the ground produces a Doppler shift that can be used to get high cross-range resolution.
ISAR = Inverse Synthetic Aperture Radar, where the radar is still (e.g. on the ground) and the target (e.g. a plane) is flying, and their relative motion produces a rotation of the target, which equally produces a Doppler shift that can be used to get high cross-range resolution.
Yeah this kind of kindergarten explanation I've seen.. This is making a bunch of simplification that aren't helpful
With a phased array you're beam forming and sweeping an area of space. Your signal returns are from the beam or side lobes. You can passively beam form on Rx as well.
But with SAR you're not beam forming. You're illuminating everything - the whole ground below you. And you get a return from everywhere all at once. Two equidistant reflectors will return signals simulatenously. If your flight path is between these two points, and the distance is always equal, how can you differentiate them?
You're digitally beam forming on the Rx somehow but I think there is more to it
> But with SAR you're not beam forming. You're illuminating everything - the whole ground below you. And you get a return from everywhere all at once. Two equidistant reflectors will return signals simulatenously. If your flight path is between these two points, and the distance is always equal, how can you differentiate them?
There are a couple conceptual ways to think about SAR. One is, in fact, as beamforming. Each position of the radar along the synthetic aperture is one element in an enormous array that's the length of the synthetic aperture itself: that's your receive array.
Regarding your question about scatterers that are equidistant along the entire synthetic aperture length: typically, SAR systems don't use isotropic antennas. And they're generally side-looking. So you would see the scatterer to one side of the radar, but not the equidistant scatterer on the other side.
If you had an isotropic antenna that saw to each side of the synthetic aperture, then the resulting image would be a coherent combination of both sides. Relevant search terms would be iso-range and iso-Doppler lines. Scatterers along the same iso-range and iso-Doppler lines over the length of the synthetic aperture are not distinguishable.
As to your question earlier in the chain, my preferred SAR book is Carrara et al. Spotlight Synthetic Aperture Radar: Signal Processing Algorithms. Given the title, it is of course geared toward spotlight (where you steer the beam to a particular point) rather than strip map or swath (where your beam is pointed at a fixed angle and dragged as you move along). It has decent coverage of the more computationally efficient Fourier-based image formation algorithms but does not really treat algorithms like the back projection that Henrik uses (I also think back projection is easier to grasp conceptually, particularly for those without a lot of background in Fourier transforms). But my book preference might just be because that's what I first learned with.
>> Your signal returns are from the beam or side lobes
You're skipping a step -- where does that beam come from? For simplicity lets think about a scene illuminated uniformly (i.e. from a single element) so that we don't get hung up on the transmit beam. I think we agree you could still sweep a receiving phased array beam across that scene. Lets further assume it's digital beamforming, so you're storing a copy of the signal incident _at every element of the array_. Not a 'beam' yet, just a bunch of individual signals.
>> you get a return from everywhere all at once
Yes! Think about each of those elements of the phased array -- they're also receiving signals from everywhere all at once.
It only becomes localized into a beam when you combine all the elements with specific phase weights. That process of combining element returns to form the beam is mathematically identical to what you do in SAR as well -- combine all your individual 'element' (individual snapshot in space) responses with some phase weights to get the return in one direction. Repeat the math in all directions to form one dimension of the image (second dimension is the radar time-of-flight bit, which is unrelated to the beamforming).
Maybe not you specifically, but I think people don't understand the 'synthetic aperture' part. Specifically, that you can ignore the time between snapshots (because the transmitter and receiver are synchronized) and act like all the snapshots the platform took across the line of flight happened simultaneously. What you're left with is the element responses to a big phased array, and you can 'beamform' using those responses.
Every month there’s a new article that improves my suburban missile defense system* and helps guarantee that my neighbors will never let their dogs poop on my lawn ever again.
Terrain mapping my neighborhood so that my rockets can navigate to the right offender has always been a challenge. Now I can just use drones!
* It’s a defense system with missiles, not a defense system against missiles. That would be silly.
I own the Tactical and Strategic Missile Guidance book. I only bought it because I have a passing interest in this stuff and really couldn't believe this sort of book is publically available.
Every terrifying technology that people worry can be propagated by AI or terrorist manuals is already sitting on a university library shelf. Most of it already available via Sci-Hub or Library Genesis. I have documents on nuclear weapons that would have been top secret 50 years ago.
I actually wanted to reply to the downstream comment, but it didn't give me a Reply link for some reason.
In any case, I've absolutely noticed how even a Raspberry Pi Zero, taken back 40 years, would be a supercomputer beyond anything that money could buy back then.
A GPU that we'd consider obsolescent today would be truly insane in 1985.
I occassionally mention to people that we can effectively have a supercomputer from 90s in our home if we so choose, but it that is lost on them since they use it for browsing at best. Tech and knowledge is only as scary as the individual wielding it. Human is the problem.
In the former case, you have close to zero for both. In the latter, you're dragging 2km of line behind a small aircraft, risking the line getting snagged by something on the ground.
A lot of anti-drone jamming is severing the wireless communication between a drone and its operator.
In most of the write-up, these drones were on pre-planned autonomous routes, and would thus not be affected. Unless you also had anti-radar installations :-)
Or hell, some kinda highly-illegal and mostly-unfeasible microwave gun or multi-watt CO2 laser that you could point at a drone and bring it down.
I find that rogue poopers are most effectively addressed with loitering munitions. It's well known that immediate feedback is critical in animal conditioning.
How about a small laser with enough power for a 100ms burst in the non-visual spectrum that vaporizes 1mm radius, 0.5mm depth of protein, through 1-5cm depth of hair?
No sense sacrificing any hardware. Zero resource attrition and imperceptible evidence of action is the name of the game.
Match that with a spot of sound out of human hearing range and you can clear the enemy of its own accord far beyond your legal and overt action spheres.
If a close neighbor’s unit stays clear but expresses its dismay regarding warning sounds too loudly, well, this works for that too.
We are talking about nuisance bears and moose, right?
I lost a little chunk of flesh to a pulsed laser, didn't even know I was injured immediately-- the wound didn't hurt until later.
Clearly the solution is laser ignition of napalm-- don't want to accidentally catch the drone on fire, so the laser can be timed to fire once the stream is clear of it.
Now we’re talking! Unfortunately I couldn’t figure out how to deploy something as viscous as napalm through my sprinkler system. I’ve been reduced to dropping it from a helicopter, the old school way.
Yes, if you can coordinate and hold their position to ~1/10th of the wavelength (gets challenging above a few GHz), and synchronize their transmitters/receivers with ps accuracy (feasible if there's no GPS interference). And somehow you're exchanging the raw signal components amongst all the platforms.
The parabolic distribution is not at all needed in this case, you would just adjust the phase at each unit based on the distribution you have.
It is a thing that's considered, mostly for very low frequencies (1-100MHz) where all the above challenges are vastly simplified, and also large antennas (potentially km) are needed for any kind of directionality.
If the drones use e.g. laser rangefinders to measure the distance to 2-3 known reflectors, and maybe to each other, with sub-mm accuracy, that may be enough.
Deploying an antenna that's effectively 50 or 100 m wide by lifting 10-20 drones, after some simple ground preparations, could be invaluable in many scenarios, especially for the military, of course.
The same technique as he uses here for synchronizing the receivers would work. Common reception and triangulation of a strong local beacon would enable positioning at much better than GNSS precision, both because of the SNR advantage itself and because you'd have more options for dealing with carrier phase ambiguity.
> Recently small FPV drone prices have dropped a lot. Small 5 and 7 inch propeller quadcopters can be bought for about 100 EUR from China (not including battery and RC controller). Despite their small size they are able to lift about 1 kg or even heavier payload which is plenty for a small radar.
The price dropped because China is selling these things by the truckload to both sides in Ukraine. China is benefitting from the economics of scale, Russia and Ukraine are each burning through on the order of 100,000 of these things each month and most components are sourced from China
I wonder what the % breakdown is for domestic vs imported drones for Ukraine?
I read recently that Ukraine was producing a lot of drones and ramping up production too, as well as using fibre-optic controlled drones to overcome electronic warfare/jamming.
You won't get any reliable numbers during wartime. I heard Ukrainian government recently mention they ordered a million.
Hundreds of small companies (around 10 employees each) in Ukraine are making and assembling drone's right now (according to journalists who filmed them in Ukraine last month). I counted at least two dozen companies in the Netherlands, probably a few hundred all over Europe. Besides the frame that holds the 4 or six rotors together all other parts are off the shelf, mostly ordered from Shenzen. You can CNC mill a carbon fiber or aluminum frame from a single plate on an x-y flatbed cnc.
I researched all this last night because I need $20K-$200k investment right now to start my own startup making unjammable autonomous kamikaze drones with 20K payload on top of 20km optical fiber spools unreeling. I think it is possible to make them lighter without fibers if you put a few thousand microprocessors in with a wafer scale integration for $500.
Of course you could just make cheap drones that kill every warm body in sight[4] indiscriminately. To disable a tank you need these fiber tethered drones with bigger payloads[3][5][6]. You cab see two fiber strands still in the air in a few frames of the video.
What you need is a Paul MacCready style development cycle for drones in the field. You need to be able to make 10 crashes per hour, fix the drone by replacing with off-the shelf components and try again. The programming should be live-coding like Squeak Smalltalk, no recompiling, just fix and run while you are using the software to edit itself [1] as Dan did in 1976[2] on this 5.88 mhz computer. We still code like this today but most programmers and managers ignore this in favor of terminals and simulated punch cards. Remember that it took humans 200.000 years to invent written language or agriculture, we just are not that smart.
[1] https://youtu.be/NqKyHEJe9_w?t=433
[2] https://www.youtube.com/watch?v=uknEhXyZgsg
[3] https://www.youtube.com/watch?v=m3uAFBzzbTc
[4] https://www.youtube.com/watch?v=TlO2gcs1YvM
[5] https://www.youtube.com/watch?v=dx5_Hzbqv9s
[6] https://www.youtube.com/watch?v=id48aVBj9Ak
hm... and why are the drones carrying the whole spool of the fiber instead of leaving the spool on the ground and unraveling it from there without the extra weight on the drone?
unraveling a stationairy ground based spool first tangles quickly if you lift two loops instead of one. Even if you had a dispencer hole you still snag loops under the dispenser that might get knots and snag the drone. Second, you would now have to drag the whole fiber from the drone down to the ground, overcoming the kilometers resistance dragging all the cable over the ground and on top of all that extra force you also have to put tension on the spool at the start to unwind it.
If you unwind the spool hanging under the drone by a rotating shaft through the spool, you do not have any tension on the fiber (but for a few grams of its weight if you unspool to slowly) and the weight of the fiber in the air even helps unspool the fiber (although you want to prevent that by speeding up the unwinding)
this may sound like a stupid question... but why not use google maps, ground images, and run a basic cnn to obtain positioning? That wouldn't require you to have it dragging/ carrying a bunch of fragile nanowire... which seems... not right?
The fiber is to (1) prevent jamming the radio control of the motors and ammunition by an operator and (2) receive a higher resolution higher frame per second multiple camera stream and (3) to ensure the operator can't be traced and targeted by triangulating the wifi antenna of the operator and (4) to allow networking by plugging in the stationairy start of the fiber into a switch connected to full internet network with thousands of kilometers of fiber between the operator and the drone so (5) the operator can be different from the drone launcher and (6) have the drone be operated by a supercomputer or datacenter with more and more accurate video frame interpretation.
Its a difference of dragging a line and just laying it out as you go. A lot less resistance to just pay out the spool so there is no tension in the wire.
As a DIYer myself I am awed by how much Henrik has managed to flesh out in terms of complexity: signal processing, hardware, GPU acceleration, and algorithmic optimizations. I wish the HN community had some award for such incredible feats.
It's a huge amount of work. It looks like at least a PhD's worth. Huge achievement for a hobbyist.
This is absolutely amazing work but I would not call him a hobbyist.
Again not diminishing the work but adjusting the expectations, this output is not from a curious guy in a shed. He is a trained Electrical Engineer working as a Senior Consultant/Scientist in RF design for a Finnish Engineering Consultancy.
This guy clearly has a breadth and depth of knowledge from his professional career which he brings with him into his out-of-office projects.
Yes, clearly this guy is an experienced RF designer.
What's impressive is that he did the RF part, the SAR data reduction part, and the drone control part. Those are different skill sets.
He is researching this stuff for s living as well.
This is actually the first time I've seen the SAR algorithm explained. Every SAR project I've seen glosses over this part.
Wonder if anyone else has seen more resources on this? Going to try to digest the linked paper.. https://topex.ucsd.edu/rs/sar_summary.pdf
And in the end it seems you can bypass a lot of the position problems with autofocusing! First time seeing this part too :))
Henrik has a blog post about a SAR radar he made from a couple years ago that goes into a bit more detail about how it works https://hforsten.com/synthetic-aperture-radar-imaging.html
Thrilled to see this because I did my PhD in radar imaging, specifically autofocusing ISAR images.
My thesis describes how the math of this all works, in chapters 3 and 4 of the PDF here: https://github.com/stevesimmons/phd-thesis-radar-imaging
Here:
SAR = Synthetic Aperture Radar, where the radar flies along a straight line and the apparent rotation of the ground produces a Doppler shift that can be used to get high cross-range resolution.
ISAR = Inverse Synthetic Aperture Radar, where the radar is still (e.g. on the ground) and the target (e.g. a plane) is flying, and their relative motion produces a rotation of the target, which equally produces a Doppler shift that can be used to get high cross-range resolution.
This site [1] has pretty approachable content generally, though it looks like the SAR page is pretty short.
I find it easiest to understand in the context of a conventional phased array, but that might not help if you don't already know how those work.
[1] https://www.radartutorial.eu/20.airborne/ab07.en.html
Yeah this kind of kindergarten explanation I've seen.. This is making a bunch of simplification that aren't helpful
With a phased array you're beam forming and sweeping an area of space. Your signal returns are from the beam or side lobes. You can passively beam form on Rx as well.
But with SAR you're not beam forming. You're illuminating everything - the whole ground below you. And you get a return from everywhere all at once. Two equidistant reflectors will return signals simulatenously. If your flight path is between these two points, and the distance is always equal, how can you differentiate them?
You're digitally beam forming on the Rx somehow but I think there is more to it
> But with SAR you're not beam forming. You're illuminating everything - the whole ground below you. And you get a return from everywhere all at once. Two equidistant reflectors will return signals simulatenously. If your flight path is between these two points, and the distance is always equal, how can you differentiate them?
There are a couple conceptual ways to think about SAR. One is, in fact, as beamforming. Each position of the radar along the synthetic aperture is one element in an enormous array that's the length of the synthetic aperture itself: that's your receive array.
Regarding your question about scatterers that are equidistant along the entire synthetic aperture length: typically, SAR systems don't use isotropic antennas. And they're generally side-looking. So you would see the scatterer to one side of the radar, but not the equidistant scatterer on the other side.
If you had an isotropic antenna that saw to each side of the synthetic aperture, then the resulting image would be a coherent combination of both sides. Relevant search terms would be iso-range and iso-Doppler lines. Scatterers along the same iso-range and iso-Doppler lines over the length of the synthetic aperture are not distinguishable.
As to your question earlier in the chain, my preferred SAR book is Carrara et al. Spotlight Synthetic Aperture Radar: Signal Processing Algorithms. Given the title, it is of course geared toward spotlight (where you steer the beam to a particular point) rather than strip map or swath (where your beam is pointed at a fixed angle and dragged as you move along). It has decent coverage of the more computationally efficient Fourier-based image formation algorithms but does not really treat algorithms like the back projection that Henrik uses (I also think back projection is easier to grasp conceptually, particularly for those without a lot of background in Fourier transforms). But my book preference might just be because that's what I first learned with.
>> Your signal returns are from the beam or side lobes
You're skipping a step -- where does that beam come from? For simplicity lets think about a scene illuminated uniformly (i.e. from a single element) so that we don't get hung up on the transmit beam. I think we agree you could still sweep a receiving phased array beam across that scene. Lets further assume it's digital beamforming, so you're storing a copy of the signal incident _at every element of the array_. Not a 'beam' yet, just a bunch of individual signals.
>> you get a return from everywhere all at once
Yes! Think about each of those elements of the phased array -- they're also receiving signals from everywhere all at once.
It only becomes localized into a beam when you combine all the elements with specific phase weights. That process of combining element returns to form the beam is mathematically identical to what you do in SAR as well -- combine all your individual 'element' (individual snapshot in space) responses with some phase weights to get the return in one direction. Repeat the math in all directions to form one dimension of the image (second dimension is the radar time-of-flight bit, which is unrelated to the beamforming).
Maybe not you specifically, but I think people don't understand the 'synthetic aperture' part. Specifically, that you can ignore the time between snapshots (because the transmitter and receiver are synchronized) and act like all the snapshots the platform took across the line of flight happened simultaneously. What you're left with is the element responses to a big phased array, and you can 'beamform' using those responses.
You can't differentiate them in that case. You'd have to fly orthogonal across the surface for~ maximum effect.
Ha, wow I’ve seen plenty of SAR images from MUCH more expensive systems that don’t look nearly as good. Incredible stuff here.
This is why I read HackerNews.
Every month there’s a new article that improves my suburban missile defense system* and helps guarantee that my neighbors will never let their dogs poop on my lawn ever again.
Terrain mapping my neighborhood so that my rockets can navigate to the right offender has always been a challenge. Now I can just use drones!
* It’s a defense system with missiles, not a defense system against missiles. That would be silly.
These might help.
Tactical and Strategic Missile Guidance, Seventh Edition https://www.amazon.com/Tactical-Strategic-Missile-Guidance-S...
Tactical missile warheads https://www.amazon.com/Tactical-Warheads-Progress-Astronauti...
Fundamentals of Astrodynamics https://www.amazon.com/Fundamentals-Astrodynamics-Second-Dov...
I own the Tactical and Strategic Missile Guidance book. I only bought it because I have a passing interest in this stuff and really couldn't believe this sort of book is publically available.
Every terrifying technology that people worry can be propagated by AI or terrorist manuals is already sitting on a university library shelf. Most of it already available via Sci-Hub or Library Genesis. I have documents on nuclear weapons that would have been top secret 50 years ago.
I actually wanted to reply to the downstream comment, but it didn't give me a Reply link for some reason.
In any case, I've absolutely noticed how even a Raspberry Pi Zero, taken back 40 years, would be a supercomputer beyond anything that money could buy back then.
A GPU that we'd consider obsolescent today would be truly insane in 1985.
I occassionally mention to people that we can effectively have a supercomputer from 90s in our home if we so choose, but it that is lost on them since they use it for browsing at best. Tech and knowledge is only as scary as the individual wielding it. Human is the problem.
I bought a detailed book about vectored thrust aircraft at a bookstore in a mall. … just a sec someone is at the door.
Woah, prices have gone up for that Missile Guidance book. Used copies were going for like $15 a couple of years ago.
$170 for 2 volume hardback set @ https://arc.aiaa.org/doi/book/10.2514/4.105845 .. fairly standard price these days for technical books.
The missile knows where it is at all times. It knows this because it knows where it isn't...
There’s that and there’s also anti-drone jamming. What a world we live in.
Ukraine and Russia are apparently building drones with fiber-optic tethers to defeat this. Like the old wire-guided missiles.
https://www.businessinsider.com/ukraines-drone-makers-produc...
I wonder why spool of fiber optic cable is on the drone vs with the operator..
Drag and fibre tension.
In the former case, you have close to zero for both. In the latter, you're dragging 2km of line behind a small aircraft, risking the line getting snagged by something on the ground.
A new cat and mouse game.
A lot of anti-drone jamming is severing the wireless communication between a drone and its operator.
In most of the write-up, these drones were on pre-planned autonomous routes, and would thus not be affected. Unless you also had anti-radar installations :-)
Or hell, some kinda highly-illegal and mostly-unfeasible microwave gun or multi-watt CO2 laser that you could point at a drone and bring it down.
Maybe old school (but sort of James Bond-esque?) but I really dig these shotgun shells that shoot nets
https://www.lesslethal.com/products/12-gauge/als12skymi-5-de...
I find that rogue poopers are most effectively addressed with loitering munitions. It's well known that immediate feedback is critical in animal conditioning.
How about a small laser with enough power for a 100ms burst in the non-visual spectrum that vaporizes 1mm radius, 0.5mm depth of protein, through 1-5cm depth of hair?
No sense sacrificing any hardware. Zero resource attrition and imperceptible evidence of action is the name of the game.
Match that with a spot of sound out of human hearing range and you can clear the enemy of its own accord far beyond your legal and overt action spheres.
If a close neighbor’s unit stays clear but expresses its dismay regarding warning sounds too loudly, well, this works for that too.
We are talking about nuisance bears and moose, right?
I lost a little chunk of flesh to a pulsed laser, didn't even know I was injured immediately-- the wound didn't hurt until later.
Clearly the solution is laser ignition of napalm-- don't want to accidentally catch the drone on fire, so the laser can be timed to fire once the stream is clear of it.
> laser ignition of napalm
Now we’re talking! Unfortunately I couldn’t figure out how to deploy something as viscous as napalm through my sprinkler system. I’ve been reduced to dropping it from a helicopter, the old school way.
Four words: Diesel engine fuel injection.
An upvote doesn’t do this justice. Just an amazing write up. Thank you.
What an amazing project! Great synthesis of skills to make such a cool project! I’m in awe!
If you need a 100 meter antenna - could one be approximated using multiple drones in a coordinated 100 meter parabolic trajectory?
Yes, if you can coordinate and hold their position to ~1/10th of the wavelength (gets challenging above a few GHz), and synchronize their transmitters/receivers with ps accuracy (feasible if there's no GPS interference). And somehow you're exchanging the raw signal components amongst all the platforms.
The parabolic distribution is not at all needed in this case, you would just adjust the phase at each unit based on the distribution you have.
It is a thing that's considered, mostly for very low frequencies (1-100MHz) where all the above challenges are vastly simplified, and also large antennas (potentially km) are needed for any kind of directionality.
No need to hold their position that accurately, just need to know, ideally in real-time.
At 6Ghz, 5cm wavelength, 1/10 would be 5mm. I think that might be a bit under regular RTK accuracy.
But at lower frequencies, maybe. Or you can do several passes with the same drone and process later :D
If the drones use e.g. laser rangefinders to measure the distance to 2-3 known reflectors, and maybe to each other, with sub-mm accuracy, that may be enough.
Deploying an antenna that's effectively 50 or 100 m wide by lifting 10-20 drones, after some simple ground preparations, could be invaluable in many scenarios, especially for the military, of course.
The same technique as he uses here for synchronizing the receivers would work. Common reception and triangulation of a strong local beacon would enable positioning at much better than GNSS precision, both because of the SNR advantage itself and because you'd have more options for dealing with carrier phase ambiguity.
Does UWB provide enough accuracy to be useful or would you need something else?
What a impressive project and great results! Thanks for sharing here on HN.
> A single-channel radar can only measure the distance to a target and is unable to detect the angle of the target.
Probably in that specific use case yes, but we have had parabolic dishes and slotted waveguide apertures for a long time now...
So, this will be seeing Russians even during the night and behind the trees?
(And soon, the Chinese drones on attack through European cities will be able to hunt civilians 24/7?)
Warfare got its 21st century upgrade for sure. This is scary but hope we’ll see some countermeasures too
This is incredible. Having had the misfortune of trying to get Sentinel 1 toolbox working, I'm now convinced it can be rewritten from scratch.
Stellar work! This is such a wonderful writeup!
Incredible engineering. Thanks for sharing it.