Flex PCB Saves Lens From The Junk Pile

There’s a piece of tech that many of us own, but very few of us have dissected. This is strange, given our community’s propensity for wielding the screwdriver, but how many of you have taken apart a camera lens. Even though many of us have a decent camera, almost none of us will have taken a lens to pieces because let’s face it, camera lenses are expensive!

[Anthony Kouttron] has taken that particular plunge though, because in cleaning his Olympus lens he tore its internal ribbon cable  from the camera connector to the PCB. Modern lenses are not merely optics in a metal tube, their autofocus systems are masterpieces of miniaturised electronics that penetrate the entire assembly.

In normal circumstances this would turn the lens from a valued photographic accessory into so much junk, but his solution was to take the bold path of re-creating the torn cable in KiCad and have it made as a flexible PCB, and to carefully solder  it back on to both connector and autofocus PCB. We applaud both the quality of his work, and thank him for the unusual glimpse into a modern lens system.

Lens repairs may be thin on the ground here, but we’ve had another in 2015 with this Nikon aperture fix.

See Starlink’s “Space Train” Before It Leaves The Station

Have you looked up into the night sky recently and seen a bizarre line of luminous dots? Have you noticed an uptick in the number of UFO reports mentioned in the news and social media? If so, you may have already been touched by what many have come to affectionately call Elon Musk’s “Space Train”: a line of tightly grouped Starlink satellites that are making their way around the globe.

Some have wondered what’s so unique about the Starlink satellites that allows them to be visible from the ground by the naked eye, but that’s actually nothing new. It’s all about being in the right place at the right time, for both the observer and the spacecraft in question. The trick is having the object in space catch the light from the Sun when it has, from the observer’s point of view, already set. It’s essentially the same reason the Moon shines at night, but on a far smaller scale.

The ISS as it travels through Earth’s night and day

The phenomena is known as “satellite flare”, and chasing them is a favorite pastime of avid sky watchers. If you know when and where to look on a clear night, you can easily spot the International Space Station as it zips across the sky thanks to this principle. NASA even offers a service which uses email or SMS to tell you when the ISS should be visible from your location.

What makes the Starlink satellites unique isn’t that we can see them from the ground, but that there’s so many of them flying in a straight line. The initial launch released 60 satellites in a far tighter formation than we’ve ever seen before; Elon even warned that collisions between the individual Starlink satellites wasn’t out of the realm of possibility. The cumulative effect of these close proximity satellite flares is a bit startling, and understandably has people concerned about what the night sky might look like when all 12,000 Starlink satellites are in orbit.

The good news is, the effect is only temporary. As the satellites spread out and begin individual maneuvers, that long line in the sky will fade away. But before Elon’s “Space Train” departs for good, let’s look at how it was created, and how you can still catch a glimpse of this unique phenomena.

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A Doppler Radar Module From First Principles

If you’ve ever cast your eyes towards experimenting with microwave frequencies it’s likely that one of your first ports of call was a cheaply-available Doppler radar module. These devices usually operate in the 10 GHz band, and the older ones used a pair of die-cast waveguide cavities while the newer ones use a dielectric resonator and oscillator on a PCB. If you have made your own then you are part of a very select group indeed, as is [Reed Foster] and his two friends who made a Doppler radar module their final project for MIT’s 6.013 Applications of Electromagnetics course.

Their module runs at 2.4 GHz and makes extensive use of the notoriously dark art of PCB striplines, and their write-up offers a fascinating glimpse into the world of this type of design. We see their coupler and mixer prototypes before they combined all parts of the system into a single PCB, and we follow their minor disasters as their original aim of a frequency modulated CW radar is downgraded to a Doppler design. If you’ve never worked with this type of circuitry before than it makes for an interesting read.

We’ve shown you a variety of commercial Doppler modules over the years, of which this teardown is a representative example.

Making Autonomous Racing Drones Lean And Mean

Recently the MAVLab (Micro Air Vehicle Laboratory) at the Technical University of Delft in the Netherlands proudly proclaimed having made an autonomic drone that’s a mere 72 grams in weight. The best part? It’s designed to take part in drone races. What this means is that using a single camera and onboard processing, this little drone with a diameter of 10 centimeters has to navigate the course, while avoiding obstacles.

To achieve this goal, they took an Eachine trashcan drone, replacing its camera with an open source JeVois smart machine vision camera and the autopilot software with the Paparazzi open UAV software. Naturally, scaling a racing drone down to this size came at an obvious cost: with its low-quality sensors, relatively low-quality camera and limited processing power compared to its big brothers it has to rely strongly on algorithms that compensate for drift and other glitches while racing.

Currently the drone is mainly being tested at a four-gate race track at TU Delft’s Cyberzoo, where it can fly multiple laps at a leisurely two meters per second, using its gate-detecting algorithms to zip from gate to gate. By using machine vision to do the gate detection, the drone can deal with gates being displaced from their position indicated on the course map.

While competitive with other, much larger autonomous racing drones, the system is still far removed from the performance of human-controlled racing drones. To close this gap, MAVLab’s [Christophe De Wagter] mentions that they’re looking at improving the algorithms to make them better at predictive control and state estimation, as well as the machine vision side. Ideally these little drones should be able to be far more nimble and quick than they are today.

See a video of the drone in action after the link.

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