Robust HRRP Recognition under Interrupted Sampling Repeater Jamming using a Prior Jamming Information-Guided Network

TL;DR

This paper presents a novel radar target recognition method that uses prior jamming information to effectively identify targets under interrupted-sampling repeater jamming, improving robustness and generalization.

Contribution

It introduces a prior-guided recognition network utilizing a point spread function to model HRRP distortion and enhance feature invariance under jamming conditions.

Findings

Outperforms state-of-the-art methods in simulated and measured data

Demonstrates strong generalization to unseen jamming parameters

Enhances recognition robustness under complex electronic countermeasures

Abstract

Radar automatic target recognition (RATR) based on high-resolution range profile (HRRP) has attracted increasing attention due to its ability to capture fine-grained structural features. However, recognizing targets under electronic countermeasures (ECM), especially the mainstream interrupted-sampling repeater jamming (ISRJ), remains a significant challenge, as HRRPs often suffer from serious feature distortion. To address this, we propose a robust HRRP recognition method guided by prior jamming information. Specifically, we introduce a point spread function (PSF) as prior information to model the HRRP distortion induced by ISRJ. Based on this, we design a recognition network that leverages this prior through a prior-guided feature interaction module and a hybrid loss function to enhance the model's discriminative capability. With the aid of prior information, the model can learn invariant features within distorted HRRP under different jamming parameters. Both the simulated and measured-data experiments demonstrate that our method consistently outperforms state-of-the-art approaches and exhibits stronger generalization capabilities when facing unseen jamming parameters.