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

Abstract

The 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, the 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 reconstruct 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-Pol reconstruction network (QPRNet) based on the Compact-Pol ISAR data characteristics. First, a group feature fusion (GFF) module is designed to collect the coupling polarimetric features between the 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 the proposed method are 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.