Compared to other sensors, lidars are not that prone to interference because:
* it only takes 1 microsecond to make a ranging measurement up to 150 m, so your detector is on for a short time
* lasers only illuminate a small spot, and the detector is also looking at a similarly small spot, so it is unlikely for two lidars to point in the same spot
Now, even if it does interfere, you may see a stream of random points pointed towards the interference source. This may happen if, say, you point a lidar directly at the sun, or if you have multiple lidars mounted on the same vehicle. Such random points are easily rejected as outliers and do not affect the vast majority of the scene. Most self driving cars (I hope) should have outlier rejection schemes that deal with outliers caused by this and other sources, such as snow, smoke, and so on.
For this reason we see many self driving cars bristling with a bunch of lidars next to each other with no problems. For example the Cruise/GM ones have five Velodynes on top.
There's a case for adding some jitter, maybe 10us, to the laser timing. That prevents any attacker from synchronizing a jammer. Common technique in military radars. If you can't synch, you can't present an illusion of something being closer than it is, and any return from a real obstacle will come in before a jamming signal from a further away transponder or mirror.
Active systems like radars have a "burn-through" short range - at some short distance, the sensing system overpowers a jammer. So if you're seeing junk at distance, but good signal at short range, you know you're being jammed and have to slow down.
Active jamming is not that effective against things that receive directionally, as people using car "radar jammers" near military bases sometimes discover. They show up on military radars as hostile targets. That's even filtering down to police LIDAR guns.
Velodyne lidars have a phase lock feature so that each lidar is out of phase with each other to prevent interference patterns. This is a bigger issue with sensors that are permanently mounted together but it'll also occur when there are many autonomous vehicles driving together.
Just another of the many edgecases to figure out before autonomous vehicles become mainstream.
I've never had a problem with a bunch of robots in the same room all using horizontal planar lidars. Mostly due to low duty cycles, I suppose, but no sensor is perfect and you've got to have some sort of noise rejection in any event.
When they talk about rejecting solar interference I'd presume, but can't be sure, that whatever they do would also help a lot with lidar on lidar interference.
The interference will most likely show up as noise. Its SPAD detectors have high noise compared to APD so the increased noise due to interference with other lidars would be minimal.
the article is a bit light on real details, but all the affordable LIDAR technology I have seen used Linear-Feedback Shift Registers, such that different devices operating at the same frequency are still on different channels.
It's unclear if this product works in the time-domain or in the frequency domain...
Shorter range lidars (<10m) tend to work in the frequency domain because you can get pretty good ranging accuracy.
Longer range lidars work in the time domain. The SPAD detectors used by Ouster create a pulse when a single photon is detected and so you're measuring the time of flight of the photon being emitted by the vscel and then being detected by the SPAD array.
* it only takes 1 microsecond to make a ranging measurement up to 150 m, so your detector is on for a short time
* lasers only illuminate a small spot, and the detector is also looking at a similarly small spot, so it is unlikely for two lidars to point in the same spot
Now, even if it does interfere, you may see a stream of random points pointed towards the interference source. This may happen if, say, you point a lidar directly at the sun, or if you have multiple lidars mounted on the same vehicle. Such random points are easily rejected as outliers and do not affect the vast majority of the scene. Most self driving cars (I hope) should have outlier rejection schemes that deal with outliers caused by this and other sources, such as snow, smoke, and so on.
For this reason we see many self driving cars bristling with a bunch of lidars next to each other with no problems. For example the Cruise/GM ones have five Velodynes on top.