  This paper first defines a class of estimation problem called simultaneous
navigation and characterization (SNAC), which is a superset of simultaneous
localization and mapping (SLAM). A SNAC framework is then developed for the
Autonomous Nanosatellite Swarming (ANS) mission concept to autonomously
navigate about and characterize an asteroid including the asteroid gravity
field, rotational motion, and 3D shape. The ANS SNAC framework consists of
three modules: 1) multi-agent optical landmark tracking and 3D point
reconstruction using stereovision, 2) state estimation through a
computationally efficient and robust unscented Kalman filter, and 3)
reconstruction of an asteroid spherical harmonic shape model by leveraging a
priori knowledge of the shape properties of celestial bodies. Despite
significant interest in asteroids, there are several limitations to current
asteroid rendezvous mission concepts. First, completed missions heavily rely on
human oversight and Earth-based resources. Second, proposed solutions to
increase autonomy make oversimplifying assumptions about state knowledge and
information processing. Third, asteroid mission concepts often opt for high
size, weight, power, and cost (SWaP-C) avionics for environmental measurements.
Finally, such missions often utilize a single spacecraft, neglecting the
benefits of distributed space systems. In contrast, ANS is composed of multiple
autonomous nanosatellites equipped with low SWaP-C avionics. The ANS SNAC
framework is validated through a numerical simulation of three spacecraft
orbiting asteroid 433 Eros. The simulation results demonstrate that the
proposed architecture provides autonomous and accurate SNAC in a safe manner
without an a priori shape model and using only low SWaP-C avionics.
