Abstract
Due to the effect of the complex scattering medium, the photons carrying target information will be attenuated when passing through scattering media, and target localization is difficult. The resolution of the target-position information from scattered images is crucial for achieving accurate target localization in environments such as dense fog in military applications. In this paper, a target localization network incorporating an attention mechanism was designed based on the robust feature resolution ability of neural networks and the characteristics of scattering formation. A training dataset with basic elements was constructed to achieve data decoupling, and then realize the position estimation of targets in different domains in complex scattering environments. Experimental validation showed that the target was accurately localized in speckle images with different domain data by the above method. The results will provide ideas for future research on the localization of typical targets in natural scattering environments.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.