RCS Diagnostic Imaging Using Parameter Extraction Technique of State Space Method. Issue 2 (7th February 2023)

• Record Type: Journal Article
• Authors: Huang, Jinhai; Liu, Xumin; Zhou, Jianjiang; Deng, Yao
• Is Part Of: Radio science. Volume 58:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-02-07
• Subjects: Radio meteorology -- Periodicals; Radio wave propagation -- Periodicals; 621.38405
• DOI: 10.1029/2022RS007565
• Languages: English
• ISSNs: 0048-6604

Abstract

Abstract: The signature extraction and processing are the key aspects of enhancing recognition ability for radar target characteristics. In this paper, to reveal the intrinsic property of the target and improve the accuracy of radar cross section (RCS), we proposed RCS diagnostic imaging technique, extracting the parameters of scattering center model by state space method (SSM), to analyze the signature of GTD‐based returns. To demonstrate the effectiveness of SSM, the comparison with estimating signal parameter via rotational invariance techniques method by the analysis of goodness‐of‐fit and root mean square error, reconstructing the RCS profile through original signal model, and employing SSM to extract the signature of specular and creeping wave from the PEC sphere. Furthermore, the RCS diagnostic imaging by SSM extracting position and amplitude is discussed, and range‐isolated pole technique specific to the creeping wave extraction is addressed the advantage of SSM. Key Points: The accuracy of parameters extracted by state space method (SSM) is better than that of estimating signal parameter via rotational invariance techniques method The feature parameters of GTD model can be extracted effectively by SSM method SSM can effectively extract specular and creeping waves from PEC sphere using range‐isolated technique