Tracking Error and Autoguiding

Problem Statement

1. Understand what is tracking error and how can autoguiding help solve this?

2. For autoguiding: what should one look for in a guide scope and guide camera? 

3. For autoguiding: what is an ideal guidescope to on-axis scope ratio in arcseconds per pixel and why?

Background

What is "tracking" and "tracking error"?

In astronomy and astrophotography, tracking error refers to the inaccuracies or deviations in the telescope mount's ability to precisely track celestial objects as they appear to move across the sky due to Earth's rotation. This error can result in star trailing or blurring in long-exposure images, reducing the overall image quality. Depending on ones location on the earth, ones tracking rate may differ. For us at the UMBC Observatory, our siderial tracking rate was calculated to be 15.042

Tracking error can arise from various sources, including mechanical imperfections, imbalances in the mount, irregularities in the gears or motors, or external factors such as wind or vibrations. Even with high-quality mounts, small imperfections or misalignments can accumulate over time and result in noticeable tracking errors. 

For successful astrophotography, it is crucial to minimize tracking error to capture sharp, detailed images. This is particularly important for long-exposure photography, where the shutter remains open for extended periods, gathering more light from faint celestial objects.

To mitigate tracking errors, astrophotographers employ several techniques:

1. Auto guiding: Autoguiding is a common technique used to minimize tracking errors. It involves using a separate guide camera and software to monitor a guide star. The software analyzes the guide star's position and sends corrections to the mount to compensate for any tracking errors. This technique helps maintain precise tracking and minimizes the impact of tracking errors on image quality.

2. Polar Alignment: Ensuring accurate polar alignment of the telescope mount is crucial. Proper polar alignment aligns the mount's axis of rotation with the Earth's axis, reducing tracking errors caused by misalignment. Tools such as polar alignment scopes, drift alignment methods, or software-assisted alignment can help achieve accurate polar alignment.

3. Mount Quality: Investing in a high-quality telescope mount can significantly reduce tracking errors. Mounts with robust construction, accurate gears, and reliable motors can provide more precise tracking and better overall performance. Computerized mounts with built-in tracking capabilities can also assist in reducing tracking errors. 

By employing these techniques and ensuring proper setup and alignment, astrophotographers can minimize tracking errors and capture high-quality images of celestial objects. For this, we will focus on autoguiding as it would appear to be the most realistic solution. For polar alignment to work, the software would require at least 10 stars to be visible in a frame which is not always the case when we are doing deep sky imaging. As for our mount quality, we have no intention of replacing our current mount and telescope as that would require a tremendous budget.

What is "autoguiding"?

Autoguiding is a technique used in astrophotography to improve the tracking accuracy of a telescope mount. It involves using a separate guiding camera to monitor a guide star and make small adjustments to the telescope's tracking to compensate for any tracking errors. This helps to capture sharp and detailed images, especially during long-exposure photography.

To set up autoguiding, you'll need a few key components:

1. Guide Camera: This is a dedicated camera that connects to your telescope. It captures images of a guide star for tracking purposes.

2. Guide Scope: A smaller telescope or a guide scope is used alongside your main imaging scope to provide a clear view of the guide star. The guide camera is attached to this scope.

3. Guiding Software: There are various software options available for autoguiding, such as PHD2 Guiding, MetaGuide, or Maxim DL. These programs analyze the guide star's position and send guiding corrections to the mount. We will be focusing on PHD2 Guiding as it is the most commonly used and most supported autoguiding software. It also integrates well with other software we use here at the observatory, such as Sharpcap, ASCOM, and N.I.N.A. 

4. Connection and Calibration: The guide camera is connected to your computer, and the guiding software communicates with both the guide camera and your mount. Before starting autoguiding, you'll need to calibrate the system by selecting a guide star and letting the software determine the necessary corrections and step sizes during its calibration phase. 

Once your autoguiding system is set up and calibrated, it continuously monitors the guide star's (x,y) camera pixel position and sends corrective commands to your mount if the pixel values change in the positive and negative x-axis or y-axis. This helps maintain precise tracking, resulting in better astrophotography images with reduced star trailing. This also allows us to take long exposures as our cameras would be enabled to stay on target for prolonged periods of time unaffected by the earth's rotation.

Methods

We know our tracking rate is bad as when we take long exposures without autoguiding, our images are littered with star trails as our camera is not staying on target. To characterize how bad our tracking rate is, we can compare two sequence captures of a known starfield. Sequence one will have tracking on and autoguiding off. The sequence will take 3 images total, each at 5 minutes apart to show how much drift occurs over 10 minutes total. Sequence two will be similar to sequence one except will have autoguiding via phd2 turned on. We can then automate this process to find the pixel coordinate of a target star at time zero (t0) which would be the first frame, and see what pixel coordinate that same target star has in the second frame (t5) and finally, its pixel coordinates in the final frame (t10).

In the future, we can automate this with the power of code to better characterize our tracking/autoguidng as well as to save time. We can also do this to extract the coordinates of multiple targets instead of just one per frame. To do this, one would need to register at least one frame to a WCS or World Coordinate System to understand which directions in the image are the rising ascension (RA) and the declination (DEC). With RA and DEC values along with the pixel scale, one can convert the pixel values of each frame to RA and DEC values. This would allow for the distance traveled to be determined in celestial coordinate space from one frame to another. One could also find the average distance traveled between two frames and note the time between the two frames. By dividing the average distance traveled by the time between frames, one can find the average distance traveled per second or minute.

Data

Results

Next Steps

Related Experiments

Citations