Research On IRFPA Nonuniformity Correction System Modeling Based On OO-TDPN

The heterogeneity of infrared focal plane arrays (IRFPA)greatly limits the performance of the imaging system. Therefore, the adjustment and correction of IRFPA is the important object of the advanced infrared detection system. Because of the superiority of the scene-based correction, it takes the scene-based BP artificial neural network correction algorithm. As it is difficult to select the parameters through the classical BP correction algorithm, and in order to realize the SOC system, it chooses a more advanced BP correction—the normalized BP artificial neural network correction—as the systematic correction.As the complexity and scale of correction algorithm increases, the difficulty of design also greatly increases. We need to take an advanced method to design systems and so in this paper, it realizes the system through the digital system design. It takes the"description—combination"systematic modeling method to conduct the top-down hierarchical modeling on the BP neural network–based IRFPA heterogeneity correction system.At first, it describes the abstracted system object classes. On the basis of the aggregation of the object classes , it builds the systematic hierarchical model; And then, it uses Verilog to describe that model and to simulate it in a simulated environment. The results proves the correctness of the model and the feasibility of the method.Based on the existing research achievements and theories, it conducts the following research projects regarding the heterogeneity correction of IRFPA:1. Research of the normalized BP artificial neural network algorithms.2. Due to the discrete and event-driven characteristic of the normalized BP neural network correction system, it combines with the advanced Petri net theory, takes the object-oriented time counting Petri net, defines and describes , and then establishes the method of modeling. This establishes the theoretical foundation of the normalized BP artificial neural network correction.3. It takes the technology of verification and analysis of the embedded system which is based on circuit simulation, and particularly studies the circuit description technology of Petri net model. It also comes up with the method and technology of using hardware description language to simulate the operation of Petri net model and to analyze and verify the function of system. This provides a simple and practical functional verification method for model.4. Combining the normalized BP artificial neural network correction algorithm with OO-TDPN, it builds model for the IRFPA heterogeneity correction system. It also uses Verilog to describe this model and the simulation of it in a simulated environment. Experiments prove the correctness of the model and the feasibility of the method.