Project SkyWatch (a.k.a. Wescam at Home) | Hacker News Reader

Project SkyWatch (a.k.a. Wescam at Home)

ianservin.com

90 pointsjjwiseman18 comments

Great project!

If you want a hardware upgrade it's actually reasonably inexpensive to build something direct drive (which is how the real sub-30kg ones work). This gives you many advantages over the plastic gear type including a much faster response time and more accurate positioning.

Look for "gimbal motors", basically a large skinny pancake brushless motor. Combine those with a storm32, simplebgc or odrive and a magnetic encoder. A 3D printer will help.

You can also have a look at low cost suppliers of cheap UAV stuff if you want something fully integrated for you. A basic Gremsy, Viewpro or Siyi isn't that much more than your Amazon thing. Various software bugs but they can be worked around. The DJI units can sometimes be had used and some of the protocols have been RE'd already.

Hey HN, thrilled my silly little project was posted here. I had been noodling on this idea for quite some time and ran into a bunch of roadblocks early on that prevented me from getting reliable control over the PTZ camera. Once those were overcome, it came together fairly quickly.

I'm looking forward to doing more experiments including integrating my own payloads (thermal and optical) with an off the shelf motion control system. I also have an automotive radar unit coming which may provide some interesting options for cueing without using ADS-B in some situations (with relatively close targets).

This is pretty cool project. Have you been able to track satellites with it, eg an ISS flyover?

I haven't but that should be fairly straightforward to do with TLE data.

Just taking this opportunity to point out (in case you haven't read it) that your project is very reminiscent of a fantastic scene from the classic cyberpunk novel Count Zero, in which the main charater Bobby catches a lift from Lucas, some kind of cybervoodoo shaman, in an autonomous limo named "Ahmed" equipped with advanced electronic countersurveilance.

---

"Lucas," Bobby said, his mouth half full of cold fried chicken, "how come it's taking us an hour and a half to get to New York? We aren't exactly crawling.

"Because," Lucas said, pausing for another sip of cold white wine, "that's how long it's taking us. Ahmed has all the factory options, including a first-rate countersurveillance system. On the road, rolling, Ahmed provides a remarkable degree of privacy, more than I'm ordinarily willing to pay for in New York. Ahmed, you get the feeling anybody's trying to get to us, listen in or anything?"

"No, sir," the voice said. "Eight minutes ago our identification panel was infra-scanned by a Tactical helicopter. The helicopter's number was MH-dash-3-dash-848, piloted by Corporal Roberto

"Okay, okay," Lucas said. "Fine. Never mind You see? Ahmed got more on those Tacs than they got on us."

This is really cool. Have you considered using something like in the below post to help the 'tracking', in case the 200ms prediction of where the aircraft should be was incorrect?

https://news.ycombinator.com/item?id=43643207

"WESCAM" seems like a crazy name for a company.

The "We" is short for Westinghouse, or at least it was: Westinghouse Steered Stabilized Camera Mount, thus WESSCAM. Then they dropped an "S".

Granted pronouncing the name is ambiguous, Wes-cam or We-scam. But they're known well enough in the industry at this point that it's not a problem for them.

It's the we-scam part that's kinda funny. But of course they don't target consumers at all so that connotation doesn't matter I guess. Professionals just go by the product specs and not brand feeling.

This is a great project: the code is super neat and the write-up very clear. I like the sousveillance aspect of it!

For a project I needed a low-latency RTSP stream as well. When reading a video stream with OpenCV, the default video buffer is quite big, which, when filling up, makes the video lag behind a second or two. It then becomes impossible to perform any interaction on it.

I wasn't familiar with the setting you use to overcome this: setting cv2.CAP_PROP_BUFFERSIZE to 1 on the VideoCapture. I am not sure, but you might get even lower latency by turning to OpenCV's GStreamer support. For me the trick was:

  gst = f"rtspsrc location={video_url} latency=0 buffer-mode=auto ! decodebin ! videoconvert ! appsink max-buffers=1 drop=true"
  self.video = cv2.VideoCapture(gst, cv2.CAP_GSTREAMER)

When testing, I also found out that the codec and image settings of the camera matter. With a h264 stream, the images came in batches of a number of frames, whereas MJPEG provided a more constant image stream with lower latency. Lastly, disabling 3D noise reduction also removed some delay.

This is a fun project that combines a cheap PTZ camera + OpenCV, Kalman filtering, PID control, and digital stabilization to not just snap photos of aircraft flying past, but do rock solid, pixel-level tracking as long as they're in sight.

And it can be combined with a source of ADS-B data so it knows what it's looking at, displaying the info on the OSD.

This is a great project and I'd use it immediately, but I'm heavily invested in ONVIF devices and have no VISCA-based cameras. Plus, I'm betting that most VISCA devices aren't weatherproof. I know that VISCA has the very nice feature of reporting back current x/y/z parameters, but that can be semi-spoofed with ONVIF by using a grid of presets and then "guessing" based on commands issued. Is that out of the question as a feature for this project? There is a massive installed base of ONVIF devices that could immediately be pulled into use.

Super interesting project and impressive engineering. It wasn't quite clear to me how he solved the problem with

> Their motors are designed for slow, dampened pans across a stage, not for tracking a jet moving at 300 knots. The mechanical and electronics latency is significant; if you simply tell the camera to “follow that plane,” by the time the motors react, the target has often moved out of the frame.

Is he able to move the motors faster than they are designed to be moved? Is this the __Control (PID + Feed-Forward Loop)__ fix?

I don't really buy this argument. What counts is angular motion as seen from the camera, not absolute speed.

In terms of angular speed, unless you have a helicopter flying super low, I doubt aircraft move significantly faster than a preacher or a teacher, which are the intended use case according to the article.

Yes! So I probably over-simplified a bit in the language there... it's not just the physical motors, but the control electronics and logic on the cam itself doing the interpolation of receive VISCA commands that reduce overall responsiveness. And that lack of responsiveness not just absolute speed that causes issues. I sort of lump that all into hardware limitations since it's not something I can directly configure.

That's really interesting. One of my unfinished projects it's a system that take input from ADSB data and from a microphone and get a picture of a flying aircraft (I am living under the approaching path of a regional airport)

Nice project! Was thinking if the Yolo library could be used for detection?

The wescam system definitely implements a digital stabilization via cropping similar to yours.

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