为使光学相关器更好地应用于自动目标识别领域，保证在较高识别速度下，具备良好的识别效果，介绍了应用于自动目标识别领域的联合变换相关器和匹配滤波相关器。针对匹配滤波相关器实现过程中的两项关键技术，在滤波器编码技术上提出了构造等相关峰综合鉴别函数以解决畸变不变识别问题。在相关峰识别技术上，针对阈值法存在的不足，提出利用BP神经网络对相关平面相关峰进行识别，采用划分感兴趣区域的方法减少了输入层神经元数目，简化了神经网络结构。借助搭建的光学相关器系统验证了该方法可对相关信号和噪声进行有效分类，提高了光学相关器的识别效果。

The joint transform correlator and Vander Lugt correlator applied in automatic target recognition are introduced in order to allow the optical correlation system to achieve a better application and guarantee the excellent recognizing effectiveness in automatic target recognition field under high-speed condition. Aiming at the key technologies in the realization process of the matched-filter correlator, the establishment of equal correlation peak synthetic discriminant functions to solve the problem appearing in the aberrance invariability recognition is brought forward. Furthermore, BP artificial neural net to recognize the correlation peak in correlation plane is put forward to solve the deficiency of threshold method in the correlation peak recognition technique. The nerve cell number of input layer is reduced and the ANN structure is simplified by dividing the interesting regions. The optical correlation system built in the lab proves the method can classify the correlation peaks from noises effectively and can improve the reliability remarkably.