Research on 2F Optical Correlator Based on Neural Network Filter for Recognizing Large-Angle Rotation Distortion Target

Abstract

It is difficult for optical correlator to recognize the target with large rotation distortion by using existing filters. To solve this problem, a new neural network model is constructed based on the physical recognition process of planar integrated 2F optical correlator. The new optical filter is optimized by training the neural network. The planar integrated 2F optical correlator can output sharp correlation peaks by using the new filter to recognize targets with arbitrary rotation distortion. Compared with the traditional OTSDF filter, the average increase of correlation peak index is up to 1402.4%, while the recognition performance of distortion invariant is also better than the new NNCRF filter. The simulation and experimental results show that the optical filter designed in this paper can effectively solve the problem of weak recognition ability of optical correlator for rotating distortion targets, especially for large angle rotating distortion targets.

Keywords

• Optical recognition
• neural network
• optical filter
• rotation distortion recognition