Deployment of Corner Reflector Arrays Based on Hybrid Attention Convolutional Neural Network

Objectives This study proposes an optimization method for the deployment of corner reflector arrays based on a hybrid attention CNN（Convolutional Neural Network）, aiming to address the arrangement challenges of sea surface corner reflector arrays. The objective is to enhance the interference capability of corner reflectors against complex targets and improve the electromagnetic protection efficacy of maritime combat platforms. Methods Initially, the electromagnetic scattering characteristics of corner reflector array geometric models under various arrangements were analyzed using the SBR (shooting and bouncing ray method), yielding one-dimensional range profiles. Subsequently, the CLEAN algorithm is applied to extract scattering centers from these one-dimensional range profiles, creating a dataset that includes data on scattering centers and radar incidence angles. Then, a prediction network model for corner reflector array arrangement is built by integrating a CNN with a hybrid attention mechanism. The dataset is input into the model for training to achieve intelligent prediction of corner reflector arrangement. Finally, the model's predictive performance is tested with different ship range profiles, and its predicted corner reflector arrays are compared with actual profiles to evaluate accuracy. Results The results show that the training loss of this network is 0.00027, and the accuracy rate is increased by 5.52% compared with the original CNN network, indicating that the model has high prediction accuracy. In scenarios with simple scattering features of ship targets, the one-dimensional range profile of the corner reflector array arranged by this method has a high correlation with that of ships, with the Pearson correlation coefficient reaching 0.9137. Even in a few complex situations, this method can still achieve interference planning by leveraging coupled scattering centers. Conclusions The research validates that the corner reflector array deployment method based on hybrid attention CNN effectively optimizes the arrangement of corner reflectors, enhances their interference capability against targets, and provides a novel technical approach for the electromagnetic protection of maritime combat platforms.