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 -