  This paper studies the suitability of neuromorphic event-based vision cameras
for spaceflight, and the effects of neutron radiation on their performance.
Neuromorphic event-based vision cameras are novel sensors that implement
asynchronous, clockless data acquisition, providing information about the
change in illuminance greater than 120dB with sub-millisecond temporal
precision. These sensors have huge potential for space applications as they
provide an extremely sparse representation of visual dynamics while removing
redundant information, thereby conforming to low-resource requirements. An
event-based sensor was irradiated under wide-spectrum neutrons at Los Alamos
Neutron Science Center and its effects were classified. We found that the
sensor had very fast recovery during radiation, showing high correlation of
noise event bursts with respect to source macro-pulses. No significant
differences were observed between the number of events induced at different
angles of incidence but significant differences were found in the spatial
structure of noise events at different angles. The results show that
event-based cameras are capable of functioning in a space-like, radiative
environment with a signal-to-noise ratio of 3.355. They also show that
radiation-induced noise does not affect event-level computation. We also
introduce the Event-based Radiation-Induced Noise Simulation Environment
(Event-RINSE), a simulation environment based on the noise-modelling we
conducted and capable of injecting the effects of radiation-induced noise from
the collected data to any stream of events in order to ensure that developed
code can operate in a radiative environment. To the best of our knowledge, this
is the first time such analysis of neutron-induced noise analysis has been
performed on a neuromorphic vision sensor, and this study shows the advantage
of using such sensors for space applications.
