Polarimetric radar target recognition framework based on LSTM

• Main Authors: Wei Chen, Liang Zhang, Jia Song, Yanhua Wang, Yang Li
• Format: Article
• Language: English
• Published: Wiley 2019-09-01
• Series: The Journal of Engineering
• Subjects: radar imaging; radar target recognition; feature extraction; synthetic aperture radar; radar polarimetry; scattering mechanism; novel polarimetric target recognition framework; long–short-term memory network; lstm; different polarimetric channels; dual-polarised high-resolution range profile recognition; features learnt; conventional features; recognition performance; polarimetric radar target recognition framework; polarimetric information; conventional polarimetric features; hand-designed
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0747

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.