实现红外焦平面阵列非均匀性自适应校正是高级红外探测系统追求的重要目标。随着校正系统算法的复杂度和 规模的增加，设计难度也大大增加。采用“描述-综合”的OO-TDPN的系统级建模方法，对基于BP神经网络的红外焦平面阵列非均匀性校正系 统自顶向下进行了有层次的建模。首先对抽象出的系统对象类进行描述；然后基于对象类的聚合建立系统的层次模型；最后采用Verilog 语言来描述此模型，并在模拟环境中进行仿真。仿真结果证明了该模型的正确性和方法的可行性。

To realize the adaptive nonuniformity correction of infrared focal plane arrays (IRFPA) is very important for an advanced infrared detection system. With the increase of the complexity and scale, the correction system algorithms are more difficult to be designed. A system-level modeling method based on OO-TDPN is used to model an IRFPA nonuniformity correction system based on the BP neural network from top to bottom hierarchically. In the modeling method, the abstracted system object class is specified; then, a hierarchical model based on polymerization of object class is established for the system; finally, the Verilog language is used to specify the model and simulation is carried out in the simulation environment. The simulation result shows that the model is correct and the method is feasible.