Reconstruction of a rocket motor time point image from limited projection data

A correction-reconstruction algorithm was developed to reconstruct a rocket motor time point image from a limited amount of projection data and known image information. Conjugate gradient optimization was used in the correction-reconstruction process. The known image information included geometry and density information about the rocket motor. To test the algorithm, a priori information was used to reconstruct two rocket motor time point images, a pre-test image and a first time point image, from a limited number of simulated projection data sets. The pre-test image is the zero time point image of the rocket motor. The simulated projection data sets were free of noise and were computed by using model images of a solid-fuel rocket motor. The pre-test and first time point images were compared after reconstructing both images with and without the use of a priori information. Error function values were used to measure the quality of the reconstructed images. Both images were better, as shown by the error function values, when a priori information was used to reconstruct them. A termination criterion for the conjugate gradient reconstruction algorithm and the correction-reconstruction process was also developed.