Infrared image simulation of ground maneuver target and scene

Infrared scene simulation has extensive applications in military and civil fields. Based on a certain experimental environment, object-oriented graphics rendering engine (OGRE) is utilized to simulate a real three-dimensional infrared complex scene. First, the target radiation of each part is calculated based on our experimental data. Then through the analysis of the radiation characteristics of targets and related material, an infrared texture library is established and the 3ds Max software is applied to establish an infrared radiation model. Finally, a real complex infrared scene is created by using the OGRE engine image rendering technology and graphic processing unit (GPU) programmable pipeline technology. The results show that the simulation images are very similar to real images and are good supplements to real data.     

Research of the ATR system based on the 3-D models and L-M BP neural network

Automatic target recognition （ATR） is an important issue for military applications, the topic of the ATR system belongs to the field of pattern recognition and classification. In the paper, we present an approach for building an ATR system with improved artificial neural network to recog- nize and classify the typical targets in the battle field. The invariant features of Hu invariant moments and roundness were selected to be the inputs of the neural network because they have the invari- ances of rotation, translation and scaling. The pictures of the targets are generated by the 3-D mod- els to improve the recognition rate because it is necessary to provide enough pictures for training the artificial neural network. The simulations prove that the approach can be implement ed in the ATR system and it has a high recognition rate and can be applied in real time.