The Small Astornomy Satellite series were a series of satellitesaimed at studying the X-ray, gamma-ray, ultraviolet, visible, andinfrared regions of the electromagnetic spectrum. SAS-1 was NASA's firstdedicated X-ray astronomy satellite and was renamed Uhuru. SAS-2 was agamma-ray telescope. SAS-3 was an X-ray astronomy space telescope.Lifetime: December 1970 (launch of SAS-1/Uhuru) - April 1979(SAS-3 ceases operations)
You may have heard the growing complaints from astronomers as companies such as SpaceX add more satellites to our sky. Astronomers are not against the communication networks that the satellites provide, but they have valid concerns for the future of ground-based explorations of the universe. And there is only so much astronomers can do on their own to mitigate the problem. A report from the 2021 conference for Dark and Quiet Skies stated:
The advantages to society that the communication constellations are offering cannot be disputed, but their impact on the pristine appearance of the night sky and on astronomy must be considered with great attention because they affect both the cultural heritage of humanity and the progress of science.
Astronomers face a variety of problems with the increasing numbers of satellites filling low-Earth orbit. Optical and near-infrared telescopes feel the impacts from these mega constellations. Some of the biggest are on wide-field surveys, longer exposures and evening and morning twilight observations when sunlight reflects off the satellites. ESO, the European Space Organization, reported these findings from a 2021 study:
Radio astronomy has some protection against interference. Radio astronomers call this spectrum management, and the Radio Communication Sector of the International Telecommunication Union (ITU-R) create regulations that help protect astronomers studying certain frequency bands and wavelength ranges. But the recent large constellations of telecommunication satellites pose new threats.
One recommendation is for satellite designs that avoid direct illumination of radio telescopes and radio-quiet zones. Also, the cumulative background electromagnetic noise created by satellite constellations should be kept below the limit already agreed to by the ITU.
Another way to mitigate the problem is for satellite operators to adjust their designs (for example, darkening the satellite). They can also operate the satellites in a way that would raise their orbits out of vision of the optical telescopes, deorbit satellites that are no longer functioning, as well as other considerations for minimizing disruption. In several cases, the satellite operators have shown willingness to cooperate on this.
Unfortunately, the companies planning these mega satellite constellations did not warn astronomers in advance. So many of these satellites were already filling the skies without any restrictions as astronomers scrambled to figure out how to save their observations and lessen the impact. Their efforts led to the creation of a new center that is collecting data from the community, astronomers and the general public, among others, to learn more about the effects on the night sky.
Three years ago SpaceX launched the first 60 Starlink satellites. The number of satellites from this and other companies is increasing exponentially and impacting the field of astronomy. During the last two years, four key workshops identified issues and recommended mitigation solutions with the help of astronomers, satellite industry folk, space lawyers and people from the general community worldwide.
Bottom line: Mega constellations of satellites can be harmful to astronomy. They mar optical and infrared images and interfere with radio astronomy. Astronomers are working to limit the negative impact.
The probability that a satellite crosses the FoV of HST can be modelled on the basis of the distribution of satellites that are visible at any point to HST, the FoV of the instruments and the exposure time, using a similar analysis to ref. 17. We use a simple model with a pure geometrical assessment, and assume that satellites are uniformly distributed with latitude and longitude and that all orbits are circular to first order. The probability that one satellite of Nsat crosses the FoV is
As an important fraction of the HST images will be affected by artificial satellites, it is important to consider mitigation strategies. The current version of DrizzlePac is not designed to correct for the satellite trails in the images, but to correct for cosmic rays (Comparison of the two methods). As mitigation for HST, one could mask out the satellite streaks (for example, with the acstools.satdet, , tool21) before combining multiple drizzled exposures with DrizzlePac. This might prove to be difficult for satellite trails that are wider than a few tens of pixels, in which case the particular exposure cannot be used for science. While deeper surveys can afford to discard one or two exposures affected by satellite trails, it will be particularly problematic for observations of bright and extended targets, such as some HST SNAP programs, where typically only a couple of exposures are available. Taking shorter exposures can alleviate some of the problems, but one will have to account for the telescope time lost with unusable images.
HST may not be the only space telescope affected by artificial satellites. Other telescopes in LEO, such as CHEOPS or NEOWISE, are also susceptible to artificial satellite trails in their images, as their orbit is below the orbit of many of the current satellites. There is a particular concern for satellites having a notable impact on observations with future telescopes in LEO having large FoVs, such as the planned Xuntian wide-field optical-IR telescope (having 300 times the FoV of HST) on the Chinese Space Station. Many space observatories are now orbiting (James Webb Space Telescope) or planned to orbit in L2 (Euclid, Plato), placing them far from artificial satellites and space debris and sparing them from the growing problem faced by telescopes in LEO and on the ground.
We analyse the occurrence of satellite trails in HST images using two different machine learning methods and two different types of HST image: individual exposures and composite images available in the eHST archives.
We applied the trained model on all 114,607 individual HST images and the model predicted that 3,157 images contain satellite trails. We inspected all the positive classifications and removed the images that were not correctly classified by the algorithm (205 cases). The main reasons for the false positive predictions were: guide star failures leading to trailing stars, diffraction spikes from bright stars or cosmic rays falsely classified as satellites. We also added 120 images that the volunteers classified as being crossed by satellites, but were not detected by the algorithm. Some of the images contain more than one satellite (the model only predicts if satellites are present in the images, but not their number). This process led to a final sample of 3,072 HST individual images containing a satellite trail and 3,228 satellite trails in total. This dataset of satellites is used for the analysis described in the main section of the paper.
We used the Google AutoML Vision multi-object-detection algorithm ( -detection/docs) to identify satellite trails in cutouts of HST composite images. The Google AutoML Vision builds a deep learning model based on a neural architecture search algorithm29. We trained the AutoML Vision model on Google Cloud with four labels: satellite, asteroid, gravitational lens arc and cosmic ray (all of these being trail-like features), thus we can detect all four types of object separately in the cutouts, as described in ref. 22. Besides the classifications, AutoML returns a bounding box for each classification, as shown in Fig. 1b.
We analysed the HST images for satellite trails using two different machine learning methods: a simple binary classifier based on the InceptionV3 model and an object-detection model in Google Cloud, AutoML. We inspected the HST individual exposures, as well as the stacked, composite HST images. The two different analysis methods show consistent results. With our machine learning classification we recovered 3,072 images with satellite trails, while with AutoML we recovered 2,935 images with satellite trails, respectively.
Finally, since we find a similar fraction of satellites in the HST individual images, which contain bright satellite trails, and in the HST composite images, where the satellite trails appear as residuals, this suggests that flagging satellites as cosmic rays and rejecting them in DrizzlePac is not sufficient to completely remove the trails. Therefore, different mitigation techniques, such as masking the satellite trail, need to be investigated for HST.
In the main article, we investigate the number of HST images containing a satellite trail s using histograms. Due to the variation in the number of observations of HST with time, by instrument and filter, we need to consider the Poisson uncertainty in the number of images with satellites, \(\sqrts\). Additionally, we assume an uncertainty in the performance of the machine learning algorithm to detect the trails. We use the F1 score of 93% that leads to an uncertainty of 0.07s. Both uncertainties are combined using the Gaussian propagation of uncertainty \(u_s=\sqrt(\sqrts)^2+(0.07s)^2=\sqrts+0.0049s^2\). We then calculate the fraction \(f=\fracsa\) of images containing a satellite trail, where a is the total number of HST images. The uncertainty in the fraction of HST images with satellites is thus
The binary machine learning classifier, as well as the code used in this work to analyse the frequency of satellite trails in HST observations and to recreate all the figures, is available on GitHub at _impact_of_satellites.
The first artificial satellite was Sputnik 1, launched by the Soviet Union in October 1957, and now more than 5,400 satellites orbit Earth at any given time. More than half are owned by U.S. companies or agencies, according to a database maintained by the Union of Concerned Scientists. Most satellites are in low-Earth orbit, less than 1,200 miles above the ground. These satellites, including the International Space Station, make a full orbit every hour and a half or so. 041b061a72