Polarimetric radar target recognition framework based on LSTM

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.