belong to a core point. DBSCAN does not divide data into parts but identifies tight clusters in any shape against the background. All the noisy points form a background group which then can be discarded. There are two main parameter:eps and Nmin. Nmin stands for minimum cluster population. We set this paramter to 5, because we don’t want to miss candidate groups with only a few points. For eps which stand for maximum distance from the core point, we used a set of experiments to choose the most suitable value. The experiments result are shown in Figure \[fig:22\]. When eps exceeds 140, the birdies loss rate drops to 0. We set eps to 145, because ETI signals will probably be a smaller cluster than our birdies during a drifting observation.

For each cluster, we apply two rules to distinguish RFI from non-RFI clusters.

1.  We calculate the sky angle between hits in a cluster, and determine whether the cluster subtends less than 1.5 times the receiver beam’s width. We use a larger than unity width because some extraterrestrial signals could be received by a beam and an adjacent beam simultaneously.

2.  We calculate the duration and bandwidth of the cluster. 