  Gravitational waves from the inspiral and coalescence of supermassive
black-hole (SMBH) binaries with masses ~10^6 Msun are likely to be among the
strongest sources for the Laser Interferometer Space Antenna (LISA). We
describe a three-stage data-analysis pipeline designed to search for and
measure the parameters of SMBH binaries in LISA data. The first stage uses a
time-frequency track-search method to search for inspiral signals and provide a
coarse estimate of the black-hole masses m_1, m_2 and of the coalescence time
of the binary t_c. The second stage uses a sequence of matched-filter template
banks, seeded by the first stage, to improve the measurement accuracy of the
masses and coalescence time. Finally, a Markov Chain Monte Carlo search is used
to estimate all nine physical parameters of the binary. Using results from the
second stage substantially shortens the Markov Chain burn-in time and allows us
to determine the number of SMBH-binary signals in the data before starting
parameter estimation. We demonstrate our analysis pipeline using simulated data
from the first LISA Mock Data Challenge. We discuss our plan for improving this
pipeline and the challenges that will be faced in real LISA data analysis.
