Abstract
Polarimetric information is of great importance for radar target recognition. Conventional polarimetric features are hand-designed based on scattering mechanism. In this study, a novel polarimetric target recognition framework based on long–short-term memory (LSTM) network is proposed. The different polarimetric channels are regarded as the sequential inputs in LSTM, and the features are extracted automatically. Experimental results on dual-polarised high-resolution range profile recognition demonstrate that the features learnt by LSTM are more discriminating than conventional features. The recognition performance of the proposed method outperforms the state-of-the-art methods as well.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
