Quad-Pol ISAR Data Reconstruction From Compact-Pol Mode Based on Polarimetric and Spatial Feature Aggregation Network

Quad polarimetric (Quad-Pol) and compact polarimetric (Compact-Pol) Inverse Synthetic Aperture Radar (ISAR) are two main configuration modes for space targets imaging. Compared with Quad-Pol ISAR mode, Compact-Pol ISAR mode can reduce radar system complexity at the price of polarimetric information loss. In order to fulfill this gap, this work dedicates to reconstructing the Quad-Pol information of space targets from the Compact-Pol mode, thereby reconciling the need for system simplicity with the retention of abundant Quad-Pol data. The main idea is to design a quad polarimetric reconstruction network (QPRNet) based on the Compact-Pol ISAR data characteristics. Firstly, a group feature fusion (GFF) module is designed to collect the coupling polarimetric features between channels of Compact-Pol ISAR data, making the network better learn the implicit mapping relationships between polarimetric channels. Then, the receptive field expansion (RFE) module is used to obtain large-scale spatial features through the network, which is beneficial to extract polarimetric modulation mechanism between adjacent components of spatial targets. Experimental studies have been carried out in Quad-Pol ISAR data reconstruction. Comparison results show that the Quad-Pol ISAR data reconstructed by proposed method is more similar to the truth. Moreover, compared with the state-of-the-arts, the mean absolute error (MAE), coherence index (COI) and peak signal-to-noise ratio (PSNR) have improved by 4.22%, 4.64% and 2.01%, respectively.