Rating system for the population of NEAs observed with the Arecibo Observatory’s planetary radar system

During decades of operations, nearly a thousand individual near-Earth asteroids (NEAs) were observed, at least half classified as potentially hazardous asteroids (PHAs). In total, 58 binary or triple NEAs have been observed with Arecibo’s radar.

The primary goals of the Arecibo planetary radar program during the years of operation were to get astrometric measurements of NEAs for orbit refinement, and to collect delay-Doppler data that would allow us to perform physical and dynamical characterization. At the time, the volume of data obtained during decades of operation in combination with new observations that had to be performed resulted in a backlog of data to be analyzed. As part of the efforts to help with the selection of data for physical and dynamical studies, we performed a complete analysis on the entire Arecibo NEA radar database to determine how many objects have sufficient information to perform detailed characterization. A preliminary assessment of Arecibo’s NEA radar database has been performed, and at least 400 NEAs observed with the planetary radar system at Arecibo are PHAs. To determine which objects would fit the requirements for future detailed characterization, we developed a rating system called image quality code. It ranges from 1 to 5, where the higher values for the quality code means that the object has high resolution delay-Doppler data with several days of observation. A quality code between 1-2 usually means that the object wasn’t resolved in delay-Doppler or had Doppler-only data . The objects with quality code 3, 4, and 5 were also categorized by their shape: round(R), elongated(E), bifurcated(B), angular(A) or irregular(I). In addition, we reinvestigated if a satellite was visible in the delay-Doppler images for the objects with quality code 4 and 5. We will present a list of objects with quality code higher than 3, and also the objects that are more suitable for future space missions based on data quality and trajectory accessibility.