An example, step by step

Let's see a step by step example of how to identify an asteroid from a group of images.

(If you don't see wee one image, click on it and it will open in a larger size)

 

Opening Aladin

To start off with, find a group of images in which a given asteroid appears.

 

 

Click on Aladin “Check with Aladin”. If your browser asks you what to open this file with, click on “open with: Sun Java Web Star”, although this will probably be the default option. (If this doesn’t work, visit the FAQ section)

 

 

Aladin will launch and start loading the images. On the right hand side of the applet you will be able to see The Stack, where the loading images appear, alongside their load percentage. 

 

The "Match" button.

Once all the images have loaded, a small window will appear recommending the use of the “match” button, which you should do.

 

The match button is located on the bottom left of the app, and means that when in “multi-view” mode, what you do to one images gets applied to all images (zoom, rotate etc.) In order to compare several images, it can be useful to use the multi-view function, which allows for 4 images to be inspected simultaneously. Once matched, a red outline will be visible around the images. 

 

 

The main use for the feature is that, when first loading an image, you will probably have to zoom in to be able to see if there is a moving object. By using this feature, you can ensure that you have zoomed in the correct amount and are inspecting the same area for all four images. 

 

 

Once you have reached the desired level of zoom, you can un-match the images.   

 

 

 

Finding an asteroid.

All images are centred to the same point: Where the cross appears. These are the approximate coordinates of where the object is, although the real position will not be on the cross. In fact, that is the point of this program: We know the estimated trajectory of the object, but due to lack of data and small changes in the trajectory when passing near other objects, this value ends up not being very precise.

When trying to locate the asteroid, bear in mind that the point must be:

• Darker than the background (darker points means more luminous asteroids)
• Close to the cross (estimated position)
  
• In different positions for each image. As these images are taken with very small time differences between one and another, objects further away, such as stars, will appear stationary, while moving objects (asteroids) will exhibit a change in position.
  

Following these criteria, it is easy to find the asteroid in these images, except for the third one where nothing can be seen.

 

 

N.B: The technique described above for identifying asteroids is the one we recommend due to its simplicity, even though it is not the only one. For example, you could create a “movie” with all the images and try to locate the object moving from one image to the other. Here’s how:

• Once all the images have been loaded, click on the “assoc” button, located in the toolbar on the right (cinema icon).
• In the assoc window, select each image from the mosaic in a different dropdown. You can adjust the delay (time between images) although the default value (400ms) is appropriate.
• Press create

Now you will see a new image appear, which is the animation of all the images selected previously. You can play, stop, forward etc. allowing you to locate the asteroid quickly and with ease. We would like to thank David Marco for suggesting this method.

 

Obtaining the Asteroid’s Coordinates.

If you click on the asteroid on the first image, the purple cross will now appear over where you have clicked, while a small red cross remains at the initial point.
 

 

Right clicking over any point on the image will copy the asteroids position to the clipboard. 

 

 

After this, simply paste this value in the RA/DEC field and change the object status to “confirmed”, as we have found the asteroid in this image.

 

Repeat this process for the other 2 images where the asteroid is visible.

 

For the third image, where nothing can be distinguished, leave the coordinate field empty and change the object status to “too faint”.

 

Finally, click on the “Save Data” button and you should see the images disappear.