  Context: The measurement of the Yarkovsky effect on near-Earth asteroids
(NEAs) is common practice in orbit determination today, and the number of
detections will increase with the developments of new and more accurate
telescopic surveys. However, the process of finding new detections and
identifying spurious ones is not yet automated, and it often relies on personal
judgment. Aims: We aim to introduce a more automated procedure that can search
for NEA candidates to measure the Yarkovsky effect, and that can identify
spurious detections. Methods: The expected semi-major axis drift on an NEA
caused by the Yarkovsky effect was computed with a Monte Carlo method on a
statistical model of the physical parameters of the asteroid that relies on the
most recent NEA population models and data. The expected drift was used to
select candidates in which the Yarkovsky effect might be detected, according to
the current knowledge of their orbit and the length of their observational arc.
Then, a nongravitational acceleration along the transverse direction was
estimated through orbit determination for each candidate. If the detected
acceleration was statistically significant, we performed a statistical test to
determine whether it was compatible with the Yarkovsky effect model. Finally,
we determined the dependence on an isolated tracklet. Results: Among the known
NEAs, our procedure automatically found 348 detections of the Yarkovsky effect
that were accepted. The results are overall compatible with the predicted trend
with the the inverse of the diameter, and the procedure appears to be efficient
in identifying and rejecting spurious detections. This algorithm is now adopted
by the ESA NEO Coordination Centre to periodically update the catalogue of NEAs
with a measurable Yarkovsky effect, and the results are automatically posted on
the web portal.
