  Redundant calibration is a technique in radio astronomy that allows
calibration of radio arrays whose antennas lie on a lattice by exploiting the
fact that redundant baselines should see the same sky signal. Because the
number of measured visibilities scales quadratically with the number of
antennas but the number of unknowns describing the individual antenna responses
and the available information about the sky scales only linearly with the array
size, the problem is always over-constrained as long as the array is big and
dense enough. This is true even for non-lattice array configurations. In this
work we study a generalized algorithm in which a per-antenna gain is replaced
with a number of gains. We show that it can successfully fit data from an
approximately redundant array on square lattice with pointing and geometry
errors, but that the models parameters are difficult to link to the quantities
of interest. We discuss the parameterization, limitations, and possible
extensions of this algorithm.
