Analysis of the optical array imaging system and construction of an adaptive imaging algorithm

In a previous article by Ikeda (1991), an optical array imaging system has been presented, which collects the array data and derives the eigenvalue with the largest eigenvalue to get images of the object. For some objects, however, the eigenvector fails to give sharply resolved object images. A preliminary study showed this problem could be solved by using a subset of the array data instead of the full set. In this paper, the integral equation describing the system is analyzed and an adaptive algorithm is constructed, to get reliable estimates of the optimum subapertures in a very short time. The algorithm is investigated thoroughly using both computer-generated and experimentally obtained array data.