An Efficient and Accurate RCS Reconstruction Technique Using Adaptive TLS-ESPRIT Algorithm

• Published in: IEEE antennas and wireless propagation letters Vol. 23; no. 1; pp. 49 - 53
• Main Authors: Zhu, Fang-Yin, Chai, Shui-Rong, Zou, Yu-Feng, He, Zhen-Xiang, Guo, Li-Xin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive algorithms; Adaptive TLS-ESPRIT algorithm; Electric conductors; Hankel matrix; Image reconstruction; Inverse synthetic aperture radar; one-dimensional (1-D) scattering center; radar cross section (RCS) reconstruction; Radar cross sections; Radar scattering; Reconstruction; Scattering; Signal processing algorithms; Statistical analysis; Statistical methods
• DOI: 10.1109/LAWP.2023.3317057
• ISSN: 1536-1225

In this letter, an adaptive total least squares-estimating signal parameter via rotational invariance techniques (TLS-ESPRIT) algorithm based on the analytical perspective is proposed to efficiently construct the scattering center model (SCM) and reconstruct the radar cross section (RCS) of a perfect electrical conductor (PEC) target. Compared with existing research, the proposed method does not require knowing the number of scattering centers, which means that it can be applied to the construction of SCMs for noncooperative targets. Compared with inverse synthetic aperture radar (ISAR) and statistical methods, this work strikes a balance between accuracy and efficiency through optimization of the core technology in the RCS reconstruction process. The effectiveness of the algorithm is verified by comparing the results derived by our method with those from the measurement.