A PSO-BP Target Localization Accuracy Enhancement Method for Airborne Optoelectronic Platforms

This study aims to address the issue of target positioning accuracy in airborne optoelectronic platforms. Firstly, the paper refines and summarizes the typical workflow for target positioning based on UAV airborne optoelectronic platforms. To enhance the target positioning accuracy of airborne optoelectronic platforms, an improved method based on the particle swarm optimization algorithm (PSO) and the backpropagation neural network (BP) is proposed. The paper begins by explaining the research background and identifying the problems. It then proposes a target localization model based on the optoelectronic platform. Subsequently, the PSO-BP method is introduced, highlighting its advantages, principles, and implementation process. Experimental results demonstrate that the PSO-BP method can effectively enhance the target localization accuracy of airborne optoelectronic platforms. The research findings of this paper hold significant theoretical importance and practical value in improving the target localization accuracy of airborne optoelectronic platforms. Additionally, they offer a new research direction for further advancements in UAV target localization. In conclusion, this comprehensive literature review provides insights into the research gap and research motivation in the field of target positioning accuracy in airborne optoelectronic platforms. The proposed PSO-BP method demonstrates its effectiveness in enhancing target localization accuracy. The findings contribute to the theoretical understanding and practical application of improving target localization in airborne optoelectronic platforms, and they also suggest avenues for future research in UAV target localization.