Practical issues in wave-front sensing by use of phase diversity.

We present the results of the phase-diversity algorithm applied to simulated and laboratory data. We show that the exact amount of defocus distance does not need to be known exactly for the phase-diversity algorithm on extended scene imaging. We determine, through computer simulation, the optimum diversity distance for various scene types.

Cramér-Rao analysis of orientation estimation: influence of target model uncertainties.

We explore the use of Cramér-Rao bound calculations for predicting fundamental limits on the accuracy with which target characteristics can be determined by using imaging sensors. In particular, estimation of satellite orientation from high-resolution sensors is examined. The analysis role that such bounds provide for sensor/experiment design, operation, and upgrade is discussed.

Cramér-Rao analysis of orientation estimation: viewing geometry influences on the information conveyed by target features.

A methodology for analyzing an imaging sensor's ability to assess target properties is developed. By the application of a Cramér-Rao covariance analysis to a statistical model relating the sensor measurements to the target, a lower bound can be calculated on the accuracy with which any unbiased algorithm can form estimates of target properties. Such calculations are important in understanding how a sensor's design influences its performance for a given assessment task and in performing feasibility studies or system architecture design studies between sensor designs and sensing modalities.