Iterative Sidelobe Suppression for Range-Doppler Imaging via Progressive Model Expansion

TY - JOUR

T1 - Iterative Sidelobe Suppression for Range-Doppler Imaging via Progressive Model Expansion

AU - Li, Kun

AU - Wu, Wenhao

AU - Ye, Hongyu

AU - Wang, Ju

AU - Wu, Siliang

N1 - Publisher Copyright: © 1965-2011 IEEE.

PY - 2026

Y1 - 2026

N2 - In range-Doppler imaging radars, the sidelobes of strong scatterers may mask weak scatterers in the matched filter outputs. Adaptive pulse compression and iterative adaptive approach pioneer a class of iterative filtering algorithms with remarkable sidelobe suppression performance. These algorithms formulate a multivariate linear model (MLM) by taking the complex scattering coefficients in all range-Doppler cells as its parameters, and solve for these parameters iteratively. As the MLM is potentially overparameterized, they incur significantly high computational costs. To address this issue, we propose a computationally efficient iterative filtering approach named iterative sidelobe suppression via progressive model expansion (PME-ISS) in this article. It adaptively formulates a series of progressively expanding MLMs based on the estimated distribution of scatterer cells (DSC), which refers to range-Doppler cells occupied by scatterers, and estimates the complex scattering coefficients of these scatterers iteratively. To ensure the compactness of the MLMs, we propose a DSC estimation method composed of identifying potential scatterer cells and removing range-Doppler cells not occupied by scatterers. A specific implementation algorithm of PME-ISS is derived, and its computational cost analysis is provided. Simulations demonstrate a computational cost reduction of multiple orders of magnitude compared with existing iterative filtering algorithms without sacrificing sidelobe suppression performance.

AB - In range-Doppler imaging radars, the sidelobes of strong scatterers may mask weak scatterers in the matched filter outputs. Adaptive pulse compression and iterative adaptive approach pioneer a class of iterative filtering algorithms with remarkable sidelobe suppression performance. These algorithms formulate a multivariate linear model (MLM) by taking the complex scattering coefficients in all range-Doppler cells as its parameters, and solve for these parameters iteratively. As the MLM is potentially overparameterized, they incur significantly high computational costs. To address this issue, we propose a computationally efficient iterative filtering approach named iterative sidelobe suppression via progressive model expansion (PME-ISS) in this article. It adaptively formulates a series of progressively expanding MLMs based on the estimated distribution of scatterer cells (DSC), which refers to range-Doppler cells occupied by scatterers, and estimates the complex scattering coefficients of these scatterers iteratively. To ensure the compactness of the MLMs, we propose a DSC estimation method composed of identifying potential scatterer cells and removing range-Doppler cells not occupied by scatterers. A specific implementation algorithm of PME-ISS is derived, and its computational cost analysis is provided. Simulations demonstrate a computational cost reduction of multiple orders of magnitude compared with existing iterative filtering algorithms without sacrificing sidelobe suppression performance.

KW - Distribution of scatterer cells (DSC)

KW - iterative filtering

KW - matched filter (MF)

KW - multivariate linear model (MLM)

KW - progressive model expansion

KW - radar

KW - range-Doppler imaging

KW - sidelobe suppression

UR - https://www.scopus.com/pages/publications/105019979329

U2 - 10.1109/TAES.2025.3624718

DO - 10.1109/TAES.2025.3624718

M3 - Article

AN - SCOPUS:105019979329

SN - 0018-9251

VL - 62

SP - 778

EP - 799

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

ER -