X. Chen et al., ACCURATE ALIGNMENT ON ASYMMETRICAL SIGNALS, Journal of vacuum science & technology. B, Microelectronics and nanometer structures processing, measurement and phenomena, 15(6), 1997, pp. 2185-2188
Existing alignment algorithms all assume that the alignment signal is
symmetrical about the correct center position. When the signal becomes
asymmetrical, these algorithms inevitably result in alignment error.
We describe a general approach to align accurately on asymmetrical sig
nals. This is achieved by incorporating learning and utilization of a
priori information. The proposed algorithm looks at some sample alignm
ent signals with known centers. The latter are provided by metrology d
ata or some other means. The algorithm builds a linear space model of
the asymmetry that is present in the sample signals. It then uses the
built model to extract the symmetrical part of alignment signals that
come from the same, well-controlled process. The extracted nearly symm
etrical signal is then used to determine the alignment position. A det
ailed algorithm is provided for each of the three steps. Computer simu
lation implementing the algorithms shows that the alignment performanc
e, both in terms of the mean and variance of the alignment error, is s
ignificantly improved compared to two examples of alignment algorithm
that do not incorporate learning. The two example alignment algorithms
used for comparison are phase detection and center of mass detection.
A physical interpretation of the linear asymmetry model is provided.
(C) 1997 American Vacuum Society.