This thesis covers a diverse set of topics related to space-based
gravitational wave detectors such as the Laser Interferometer Space
Antenna (LISA). The core of the thesis is devoted to the preprocessing
of the interferometric link data for a LISA constellation, specifically
developing optimal Kalman filters to reduce arm length noise due to
clock noise. The approach is to apply Kalman filters of increasing
complexity to make optimal estimates of relevant quantities such as
constellation arm length, relative clock drift, and Doppler frequencies
based on the available measurement data. Depending on the complexity of
the filter and the simulated data, these Kalman filter estimates can
provide up to a few orders of magnitude improvement over simpler
estimators. While the basic concept of the LISA measurement (Time Delay
Interferometry) was worked out some time ago, this work brings a level
of rigor to the processing of the constellation-level data products.
The thesis concludes with some topics related to the eLISA such as a new
class of phenomenological waveforms for extreme mass-ratio inspiral
sources (EMRIs, one of the main source for eLISA), an octahedral
space-based GW detector that does not require drag-free test masses, and
some efficient template-search algorithms for the case of relatively
high SNR signals.