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PSO-based fine polarimetric decomposition for ship scattering characterization
ISPRS Journal of Photogrammetry and Remote Sensing ( IF 10.6 ) Pub Date : 2024-12-05 , DOI: 10.1016/j.isprsjprs.2024.11.015 Junpeng Wang, Sinong Quan, Shiqi Xing, Yongzhen Li, Hao Wu, Weize Meng
ISPRS Journal of Photogrammetry and Remote Sensing ( IF 10.6 ) Pub Date : 2024-12-05 , DOI: 10.1016/j.isprsjprs.2024.11.015 Junpeng Wang, Sinong Quan, Shiqi Xing, Yongzhen Li, Hao Wu, Weize Meng
Due to the inappropriate estimation and inadequate awareness of scattering from complex substructures within ships, a reasonable, reliable, and complete interpretation tool to characterize ship scattering for polarimetric synthetic aperture radar (PolSAR) is still lacking. In this paper, a fine polarimetric decomposition with explicit physical meaning is proposed to reveal and characterize the local-structure-related scattering behaviors on ships. To this end, a nine-component decomposition scheme is first established through incorporating the rotated dihedral and planar resonator scattering models, which makes full use of polarimetric information and comprehensively considers the complex structure scattering of ships. In order to reasonably estimation the scattering components, three practical scattering dominance principles as well as an explicit objective function are raised, and a particle swarm optimization (PSO)-based model inversion strategy is subsequently presented. This not only overcomes the underdetermined problem, but also improves the scattering mechanism ambiguity by circumventing the constrained estimation order. Finally, a ship indicator by linearly combining the output scattering contribution is further derived, which constitutes a complete ship scattering interpretation approach along with the proposed decomposition. Experiments carried out with real PolSAR datasets demonstrate that the proposed method adequately and objectively describes the scatterers on ships, which provides an effective way to ship scattering characterization. Moreover, it also verifies the feasibility of fine polarimetric decomposition in a further application with the quantitative analysis of scattering components.
中文翻译:
基于 PSO 的精细极化分解用于船舶散射表征
由于对舰内复杂子结构散射的估计和认识不足,目前仍缺乏一种合理、可靠、完整的极化合成孔径雷达(PolSAR)舰船散射表征解译工具。在本文中,提出了一种具有明确物理意义的精细极化分解,以揭示和表征船舶上与局部结构相关的散射行为。为此,首先通过结合旋转二面体和平面谐振器散射模型,建立了九分量分解方案,充分利用极化信息,综合考虑了船舶的复杂结构散射。为了合理估计散射分量,提出了 3 个实用的散射优势原则和一个明确的目标函数,随后提出了一种基于粒子群优化 (PSO) 的模型反演策略。这不仅克服了欠定问题,而且通过规避约束估计阶数改善了散射机制的模糊性。最后,进一步推导了线性组合输出散射贡献的船舶指标,该指标与所提出的分解一起构成了完整的船舶散射解释方法。使用真实 PolSAR 数据集进行的实验表明,所提方法充分、客观地描述了舰船上的散射体,为舰船散射表征提供了一种有效的途径。此外,它还验证了精细极化分解在进一步应用中通过散射分量的定量分析的可行性。
更新日期:2024-12-05
中文翻译:
基于 PSO 的精细极化分解用于船舶散射表征
由于对舰内复杂子结构散射的估计和认识不足,目前仍缺乏一种合理、可靠、完整的极化合成孔径雷达(PolSAR)舰船散射表征解译工具。在本文中,提出了一种具有明确物理意义的精细极化分解,以揭示和表征船舶上与局部结构相关的散射行为。为此,首先通过结合旋转二面体和平面谐振器散射模型,建立了九分量分解方案,充分利用极化信息,综合考虑了船舶的复杂结构散射。为了合理估计散射分量,提出了 3 个实用的散射优势原则和一个明确的目标函数,随后提出了一种基于粒子群优化 (PSO) 的模型反演策略。这不仅克服了欠定问题,而且通过规避约束估计阶数改善了散射机制的模糊性。最后,进一步推导了线性组合输出散射贡献的船舶指标,该指标与所提出的分解一起构成了完整的船舶散射解释方法。使用真实 PolSAR 数据集进行的实验表明,所提方法充分、客观地描述了舰船上的散射体,为舰船散射表征提供了一种有效的途径。此外,它还验证了精细极化分解在进一步应用中通过散射分量的定量分析的可行性。