HRRP target identification method based on joint feature Extraction and Stacking model classification

This paper introduces a radar target recognition method for High Resolution Range Profile (HRRP). The method uses ID Convolutional Neural Network (ID-CNN) to extract the deep features of HRRP, and combining with a variety of non-parametric features of HRRP for feature-level fusion, so as to obtain a more comprehensive feature characterization. In addition, the Stacking integration model is used to integrate multiple basic classifiers at the decision level, further improving the recognition accuracy and robustness of the model. Finally, the recognition and classification results are obtained through experiments with simulation data and measured data, and the performance of the proposed method is further verified by comparison with other deep learning algorithms, indicating that the method has certain practical application value in the field of radar target recognition.