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what was that object?


darthvader

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I was looking at Jupiter the other night through my 15 x 70 bins (i think it was sun night)

I guess it was around 10pm

A small object entered my field of view moving from left to right approx S to W?

It was about the size of a star(relatively!) and was moving pretty quick (much faster than planes I see going overhead) and moving in what appeared to be a straight line.

I thought it might have been the ISS but from what I've read since I think it was too small? I 'm pretty sure it wasn't a meteor as I've seen a few of those and they seem to move much quicker.

Any ideas what it was? A satellite maybe or aliens!

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When ever i need to check those odd sightings i use stellarium and wind the time back where you can then see which object it is. Spotted the ISS a couple of times and lots of satellites.

Sent from my Windows Phone 8X by HTC using Tapatalk

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Could have been the satellite S3 which passed Jupiter at 9.52pm or Argos which passed at 10pm. Both heading vaguely in that direction.

Times are based on Edinburgh settings, just check heavens-above.com.

Mark

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My guess is Envisat. From your pov (Ellastone near Derby?) it had a visible pass near, almost across)  Jupiter the 25.march at 10pm. ( heavens-above).

But I might be terrible wrong (I very often am..)

You can google Envisat, theres even a pic of that kind of satelitte.

Rune

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Thanks guys - yep about 20 miles from Derby Pondus

I guess ill never really know exactly what it was as im not sure exactly what time it was!

At least I know what to look for now

I guess all those satellites must play havoc with long exposure photography for you AP guys and gals?

My new 200p dob arrived today just finished putting it together must say the instructions weren't very clear but managed to put it together right i hope! And guess what it's now completely clouded over :(

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One rather scary night I saw a small star like object shoot over the sky, then..... it stopped dead, stayed there for around 30 seconds, then shot off so fast it basically vanished in a second. I'd have been my usual skeptic self had it not been for a few friends who were stood right with me and watched this happen. I love just looking into the dark skys, I don't care what anyone says, we certainly are not alone, ive seen it with my own eyes.

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I guess all those satellites must play havoc with long exposure photography for you AP guys and gals?

Not really. It is pretty common to end up with at least one trail on a sub, be that satellite or aircraft lights and two or more is not that unusual.  By stacking multiple exposures it is very easy to reject the trails from the final image.  Since they only appear in a given place on one out of n images, you can remove them using basic maths.

Once the images have been registered (aligned) so that each given pixel in all the images covers the same spot in the sky, you can:

- Do a simple average of all the images.  This is not ideal as the trails will still contribute something to the final image.  The more images you average the fainter it becomes.

- Take the median value of the corresponding pixels in all your images.  This works really well at removing trails since the median will reject any outliers completely (you're just taking the value nearest the middle of the set, and any trails will be well away from the middle).  The downside with median is that you're not taking full advantage of the information in the rest of the pixels, so you won't get as close to the 'true' value of that pixel.

- The usual approach is to take a weighted average of each pixel (so you'd assess each image, e.g. by calculating how much noise there is in it, or even more simply how long the exposure was).  Pixels from better images are multiplied by a larger weighting factor and contribute more to the final average and thus get you closer to the 'true' value.

- As we now know, averaging doesn't deal with trails and other artefacts, so you then need to add in a pixel rejection algorithm to remove any outliers before you do the average.  There are lots of different ways of rejecting pixels, and the most suitable is usually down to how many images you have in total:

- Minimum/maximum clipping is the most basic method.  You just ignore the brightest and darkest values in each set of pixels (so maybe the brightest and darkest, the two brightest and darkest, or three, etc.)  It is not very good at keeping the 'good' data though since you throw away some pixels for each set and the vast majority of those rejected will not be trails or other outliers.

- Percentile clipping is the next simplest method and highly effective on small sets of images.  You just ignore any pixels that are more than x% brighter or darker than the average value for that set. By increasing the value of x you can find the point where the trails disappear but still keep most of the good data for the average.

- Sigma clipping is the next step up if you have a few more images.  You calculate the standard deviation of each set of pixels and reject those that are more than x standard deviations away from the average value. It is more accurate than percentile clipping, but does need a reasonably large set of images to work.  Again you play with the value of x to find the ideal point to remove trails and keep the most data you can.

- More advanced processing packages offer further refinements on sigma clipping, such as Winsorized sigma clipping.  It works the same as above, except you don't throw away any rejected pixels but replace them with the next nearest pixel value in the set.

-  There are other more complicated algorithms that can be used, but the most useful is linear fit clipping, which attempts to compensate for differences in brightness between images (e.g. if the light pollution in the image changes as your target rises in the sky, or if you have images with different amounts of moon glow affecting them).

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Wow now that's what I call a comprehensive answer!

That's what I like about this forum it doesn't matter how many people ask noob questions you always get a good answer.

A lot of forums treat you like scum especially PC help ones and deride questions asked before and sarcastically point you towards Google to search for the answer yourself.

Give yourselves a pat on the back you all deserve it for being Such a friendly helpful lot :-)

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