Backtracking Dichotomous-Least Squares-Based Sidelobe Suppression Algorithm for Multiple Targets With Straddling

TY - JOUR

T1 - Backtracking Dichotomous-Least Squares-Based Sidelobe Suppression Algorithm for Multiple Targets With Straddling

AU - Ning, Chen

AU - Tian, Jing

AU - Zhang, Yanjun

AU - Xia, Xiang Gen

AU - Cui, Wei

AU - Wu, Siliang

N1 - Publisher Copyright: © 1965-2011 IEEE.

PY - 2025/10

Y1 - 2025/10

N2 - The performance of sidelobe suppression methods based on on-grid signal models deteriorates significantly when target parameters deviate from the predefined discrete parameter grids. To address this issue, we propose a backtracking dichotomous-least squares (BD-LS) algorithm based on the minimum residual energy criterion. BD-LS iteratively estimates the parameters of targets whose powers are higher than the threshold used for stopping the iteration, in the descending order of the target powers. During each iteration, the coarse position of the strongest target is first estimated based on the 2-D matched filtering results of the residual signal, and then the straddling offset of the target is estimated according to the minimum residual energy criterion and the dichotomous iterative strategy. After the straddling offsets of all targets are accurately estimated, the complex amplitudes of targets are simultaneously estimated by using the LS algorithm. To mitigate the impact of target interference on the estimation of straddling offsets, multiple backtracking refinements are adopted. In each backtracking refinement processing, the straddling offsets of all the targets above a given threshold are sequentially refined by using the obtained straddling offset estimates of targets as prior information. Simulation results show that BD-LS can effectively suppress the sidelobes of targets with range–Doppler-straddling and accurately estimate the straddling offsets and powers of targets. Compared to the straddling-robust iterative adaptive filtering algorithm, BD-LS provides better sidelobe suppression performance and more accurate estimation of the straddling offsets and powers of targets with lower computational complexity in multitarget scenarios. The effectiveness of the proposed method is demonstrated by both simulated and real data.

AB - The performance of sidelobe suppression methods based on on-grid signal models deteriorates significantly when target parameters deviate from the predefined discrete parameter grids. To address this issue, we propose a backtracking dichotomous-least squares (BD-LS) algorithm based on the minimum residual energy criterion. BD-LS iteratively estimates the parameters of targets whose powers are higher than the threshold used for stopping the iteration, in the descending order of the target powers. During each iteration, the coarse position of the strongest target is first estimated based on the 2-D matched filtering results of the residual signal, and then the straddling offset of the target is estimated according to the minimum residual energy criterion and the dichotomous iterative strategy. After the straddling offsets of all targets are accurately estimated, the complex amplitudes of targets are simultaneously estimated by using the LS algorithm. To mitigate the impact of target interference on the estimation of straddling offsets, multiple backtracking refinements are adopted. In each backtracking refinement processing, the straddling offsets of all the targets above a given threshold are sequentially refined by using the obtained straddling offset estimates of targets as prior information. Simulation results show that BD-LS can effectively suppress the sidelobes of targets with range–Doppler-straddling and accurately estimate the straddling offsets and powers of targets. Compared to the straddling-robust iterative adaptive filtering algorithm, BD-LS provides better sidelobe suppression performance and more accurate estimation of the straddling offsets and powers of targets with lower computational complexity in multitarget scenarios. The effectiveness of the proposed method is demonstrated by both simulated and real data.

KW - Dichotomous iterative strategy

KW - least squares

KW - sidelobe suppression

KW - straddling effect

UR - https://www.scopus.com/pages/publications/105007643882

U2 - 10.1109/TAES.2025.3576079

DO - 10.1109/TAES.2025.3576079

M3 - Article

AN - SCOPUS:105007643882

SN - 0018-9251

VL - 61

SP - 12678

EP - 12701

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

IS - 5

ER -