  Space-based coronagraphs for future earth-like planet detection will require
focal plane wavefront control techniques to achieve the necessary contrast
levels. These correction algorithms are iterative and the control methods
require an estimate of the electric field at the science camera, which requires
nearly all of the images taken for the correction. We demonstrate a Kalman
filter estimator that uses prior knowledge to create the estimate of the
electric field, dramatically reducing the number of exposures required to
estimate the image plane electric field. In addition to a significant reduction
in exposures, we discuss the relative merit of this algorithm to other
estimation schemes, particularly in regard to estimate error and covariance. As
part of the reduction in exposures we also discuss a novel approach to
generating the diversity required for estimating the field in the image plane.
This uses the stroke minimization control algorithm to choose the probe shapes
on the deformable mirrors, adding a degree of optimality to the problem and
once again reducing the total number of exposures required for correction.
Choosing probe shapes has been largely unexplored up to this point and is
critical to producing a well posed set of measurements for the estimate.
Ultimately the filter will lead to an adaptive algorithm which can estimate
physical parameters in the laboratory and optimize estimation.
