Mueller Matrix Decomposition and Image for Non-Destructive Testing of UAVs Skin

Autor: Hongzhe Li, Lin Li, Xiaolei Yu, Delong Meng, Ciyong Gu, Zhenlu Liu, Zhimin Zhao
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Applied Sciences, Vol 13, Iss 4, p 2609 (2023)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app13042609
Popis: Recently, Mueller matrix polarimetry (MMP) has been widely applied in many aspects, such as radar target decomposition, monitoring the glucose level, tissue diagnostics, biological samples, etc., but it is still challenging for the complex light–matter interactions of rough surfaces and non-uniform structures such as 3D composite materials. In this work, a unitary matrix-based Mueller matrix decomposition (UMMMD) is proposed for non-destructive testing (NDT) of unmanned aerial vehicles (UAVs) skin. The decomposition model is constructed by the unitary matrix transformation of coherency matrices. In the model, the non-uniform depolarization caused by multiple scattering is quantified with the depolarization matrix and the entropy. From this model, the Mueller matrix of multiple scattering media can be completely decomposed. The proposed method can provide more polarization information than some traditional methods for multiple scattering under different polarization states. The contrast of the obtained polarization image can be improved by about 13 times compared to that of the original image. In addition, the key features of UAV skin such as deformation, shear angles, and density are obtained. The shear angles vary from 17° to 90°, and the average density is about 20/cm2. The provided experimental results show that this method is effective for the NDT of UAVs skin. The method also shows great potential for applications in target decomposition, NDT of 3D composite materials, 3D polarization imaging, light–matter interactions of non-uniform complex structures, etc.
Databáze: Directory of Open Access Journals