Enhanced Detection of Low-Observable Maneuvering Targets Based on FDGRFT and Lévy Golden Sparrow Search Algorithm

TY - JOUR

T1 - Enhanced Detection of Low-Observable Maneuvering Targets Based on FDGRFT and Lévy Golden Sparrow Search Algorithm

AU - Sun, Yuxian

AU - Liu, Quanhua

AU - Li, Yuanshuai

AU - Zheng, Ziming

AU - Chang, Shaoqiang

N1 - Publisher Copyright: © 1963-2012 IEEE.

PY - 2026

Y1 - 2026

N2 - Low-observable maneuvering targets significantly challenge radar detection due to their low radar cross section (RCS) and high maneuverability. Within the dechirp-receiving radar system, the conventional dechirp generalized Radon–Fourier transform (DGRFT) method can measure the motion parameters of low-observable maneuvering targets through grid-based matching, which imposes a substantial computational burden. Moreover, this method performs suboptimally when the actual motion parameters deviate significantly from the discrete grid points. To overcome these limitations, this article first introduces a novel frequency-domain formulation, termed fast-frequency DGRFT (FDGRFT), which achieves computational reduction by deriving an efficient frequency-domain filter bank structure for parameter measurement. Furthermore, to address the suboptimal performance of grid-based DGRFT for off-grid parameters and the limitations of prior optimization attempts, a newly developed metaheuristic, the Lévy golden sparrow search algorithm (LGSSA), is proposed and integrated with FDGRFT. This synergistic LGSSA-FDGRFT method enables more accurate and robust measurement of target motion parameters, while further reducing computational complexity. The effectiveness of the proposed detection method for low-observable maneuvering aerial targets is validated through both simulations and measured data.

AB - Low-observable maneuvering targets significantly challenge radar detection due to their low radar cross section (RCS) and high maneuverability. Within the dechirp-receiving radar system, the conventional dechirp generalized Radon–Fourier transform (DGRFT) method can measure the motion parameters of low-observable maneuvering targets through grid-based matching, which imposes a substantial computational burden. Moreover, this method performs suboptimally when the actual motion parameters deviate significantly from the discrete grid points. To overcome these limitations, this article first introduces a novel frequency-domain formulation, termed fast-frequency DGRFT (FDGRFT), which achieves computational reduction by deriving an efficient frequency-domain filter bank structure for parameter measurement. Furthermore, to address the suboptimal performance of grid-based DGRFT for off-grid parameters and the limitations of prior optimization attempts, a newly developed metaheuristic, the Lévy golden sparrow search algorithm (LGSSA), is proposed and integrated with FDGRFT. This synergistic LGSSA-FDGRFT method enables more accurate and robust measurement of target motion parameters, while further reducing computational complexity. The effectiveness of the proposed detection method for low-observable maneuvering aerial targets is validated through both simulations and measured data.

KW - Coherent integration

KW - dechirp receiving

KW - low-observable maneuvering targets

KW - metaheuristic algorithm

KW - motion parameter measurement

UR - https://www.scopus.com/pages/publications/105025662021

U2 - 10.1109/TIM.2025.3645904

DO - 10.1109/TIM.2025.3645904

M3 - Article

AN - SCOPUS:105025662021

SN - 0018-9456

VL - 75

SP - 1

EP - 16

JO - IEEE Transactions on Instrumentation and Measurement

JF - IEEE Transactions on Instrumentation and Measurement

ER -