Monitoring the operational environment of active asteroid (101955) bennu

The OSIRIS-REx spacecraft has observed the release of small particles from the surface of asteroid (101955) Bennu. New techniques and tools have been developed to detect, track, and characterize the particles. Many of the techniques and tools were borrowed from telescopic observations of moving objects, such as asteroids and comets. In particular, the automated detection software of the Catalina Sky Survey was modified to search OSIRIS-REx imagery. Introduction. “Active asteroids” are defined as small bodies on asteroidal orbits showing evidence of mass loss [1]. The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRISREx) mission is investigating near-Earth asteroid (101955) Bennu in advance of collecting a regolith sample to bring back to Earth for analysis. During the course of routine optical navigation imaging by the Touch And Go Camera System (TAGCAMS) [2], Bennu was observed to be an “active asteroid,” experiencing multiple mass loss events [3]. Hundreds of resulting particles have been observed in the operational environment around Bennu. The particles inhabit a range of different trajectories. Some particles completely escape the Bennu system and enter heliocentric orbit. Others have been observed on suborbital trajectories lasting hours with a few long-lived particles completing multiple circuits about Bennu before impacting back onto the asteroid’s surface. The particles are more than a scientific curiosity, as the success of the mission depends on rapidly assessing the safety of the near-Bennu environment. A number of techniques from the optical navigation, astronomical, and asteroid surveying communities were introduced to support scientific investigations and solve the situational awareness problem of particle monitoring. Particle Detection. Particle detection data consist of pairs of images taken ~2–3 minutes apart. These image pairs are repeated once every ~12 to ~120 minutes. Various techniques have been used to monitor the particles in this dataset. One path to particle detection utilizes the Goddard Image Analysis and Navigation Tool (GIANT), which was originally tasked with supporting optical navigation operations and was modified to identify particles [4]. This presentation will focus on additional particle detection paths using astronomical methods borrowed from ground-based asteroid surveys. Visual Inspection. The most basic form of particle detection is the manual identification of moving objects based on their motion relative to fixed background stars, colloquially referred to as ‘blinking’ images. This method is used when it is quicker than automated software (for the quick identification of ejection events containing ~20+ particles) or when image data is not optimal for automated detection (time between pairs is large enough that particles are only visible in one or two images). A second manual technique is the visual inspection of an image created by the division of one image in a pair by the other image in a pair. A moving object in a differenced image appears as a positive-negative pair of sources. For most particle images, asteroid Bennu is also in the field of view. The visibility of particles is enhanced by minimizing the stray light from Bennu through the production of a Gaussian convolved image. This technique is a variant of the classical unsharp masking and is commonly used to enhance the visibility of fine features within the coma of comets [5]. The manual techniques suffer from some major limitations. One, manual inspection for solitary particles is very time-intensive. Two, they are heavily dependent on the experience and time-dependent sensitivity of the human inspector. Automated detection software. In order to produce a quicker, consistent, and modellable solution for finding all types of particles, an automated software approach was developed by the Catalina Sky Survey (CSS), which conducts a search for asteroids and comets utilizing a number of ground-based telescopes. Their search algorithms are conducted on two sequential image pairs, consisting of four images at a time. The CSS software is used in addition to the GIANT tool. The TAGCAMS instruments have a significant barrel, or fisheye, lens distortion of up to 160 pixels. The ISIS3 system is used to produce undistorted TAGCAMS images and convert them to FITS images. The automated