  The new generation of radio synthesis arrays, such as LOFAR and SKA, have
been designed to surpass existing arrays in terms of sensitivity, angular
resolution and frequency coverage. This evolution has led to the development of
advanced calibration techniques that ensure the delivery of accurate results at
the lowest possible computational cost. However, the performance of such
calibration techniques is still limited by the compact, bright sources in the
sky, used as calibrators. It is important to have a bright enough source that
is well distinguished from the background noise level in order to achieve
satisfactory results in calibration. We present "clustered calibration" as a
modification to traditional radio interferometric calibration, in order to
accommodate faint sources that are almost below the background noise level into
the calibration process. The main idea is to employ the information of the
bright sources' measured signals as an aid to calibrate fainter sources that
are nearby the bright sources. In the case where we do not have bright enough
sources, a source cluster could act as a bright source that can be
distinguished from background noise. We construct a number of source clusters
assuming that the signals of the sources belonging to a single cluster are
corrupted by almost the same errors, and each cluster is calibrated as a single
source, using the combined coherencies of its sources simultaneously. This
upgrades the power of an individual faint source by the effective power of its
cluster. We give performance analysis of clustered calibration to show the
superiority of this approach compared to the traditional unclustered
calibration. We also provide analytical criteria to choose the optimum number
of clusters for a given observation in an efficient manner.
