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

An automated procedure for the detection of the Yarkovsky effect and results from the ESA NEO Coordination Centre