HRRP Reconstruction Method for Coded Interrupted Sampling Radar Echoes Based on Multi-Frame Sequential Priors

Abstract

High-resolution range profile (HRRP) reconstruction is essential for extracting range-direction scattering characteristics in wideband radar remote sensing, particularly in synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) imaging. Coded interrupted sampling (CIS) can improve radar low probability of intercept (LPI) performance by controlling signal transmission with a binary sequence. However, the reduced number of valid echo samples may degrade HRRP reconstruction, especially under low-duty-ratio and low signal-to-noise ratio (SNR) conditions. Conventional orthogonal matching pursuit (OMP) processes each frame independently and ignores the inter-frame continuity of scattering-center positions, which may lead to false selections and missed detections. To address this problem, this paper proposes a candidate-interval-assisted orthogonal matching pursuit (CI-OMP) algorithm based on multi-frame sequential priors. Stable scattering-center positions are extracted from historical reconstruction results and expanded into candidate intervals to guide atom matching in the current frame. Simulation results show that CI-OMP outperforms standard OMP in terms of normalized mean squared error (NMSE), tolerant support recovery rate (Tol-SRR), and peak-to-sidelobe ratio (PSLR). At a duty ratio of 0.20, CI-OMP reduces the NMSE by 1.71 dB and improves the PSLR by 7.56 dB compared with OMP. In addition, the candidate-interval strategy reduces the atom-search range by approximately 54–75% under different duty ratios and by approximately 50–83% under different SNRs, demonstrating improved search efficiency. These results demonstrate that CI-OMP improves the accuracy, robustness, and search efficiency of HRRP reconstruction for CIS radar echoes, particularly under low-duty-ratio and low-to-medium-SNR conditions.