Adaptive optical correlation using neural network approaches

This paper reviews work on binary phase-only (BPOF) and ternary phase-amplitude (TPAF) correlation and highlights recent investigations of neural network approaches for augmenting correlation-based hybrid (optical/electronic) automatic target recognition systems. The theory and implementation of BPOF and TPAF correlation using available spatial light modulators is reviewed, including recent advances in smart TPAF formulations. Results showing the promise of neural networks for enhancing correlation system operation in the areas of estimating distortion parameters, adapting filters, and improving discrimination are presented and discussed.