基于人工神经网络的红外探测效果评估

红外探测设备是红外系统中的重要组成部分，对其性能评估具有实际意义。分析研究了影响红外探测效果的主要因素，选取环境温度、相对湿度、能见度、辐通量、目标高度和探测距离为评价指标。针对神经网络良好的非线性映射功能及高精度的特点，构建了BP网络评估模型，实验表明，该方法简单有效，评估精度较高，具有很强的实际应用价值。

Evaluation of Infrared Detector Equipment Index Based on BP Network

Infrared detector equipment is an important part of infrared system, and to evaluate itsperformance has a practical significance. The main impact factor is analyzed, and environment tempera-ture, relative humidity, visibility, radiant flux, target height and detection range are selected for evalua-tion index. In view of the nonlinear mapping function of neural network is good and the characteristics ofhigh precision,the BP network evaluation model is set up, the experiment expresses that the method issimple and effective, evaluation precision is high, and has more actual application value.