Crop characterization using Compact-Pol Synthetic Aperture Radar (CP-SAR) data is of prime interest with the rapid advancements of SAR systems towards operational applications. It is noteworthy that as a good compromise between the dual and quad-polarized SAR systems, the CP-SAR offer advantages in terms of the larger swath and lower data rate. The m − χ CP decomposition considers two out of the three Stokes child parameters: degree of polarization (m), ellipticity (χ), and orientation angle (ψ) to describe the polarized part of the quasi-monochromatic partially polarized wave. An improvement in the scattering powers was proposed in the S − Ω decomposition, which takes into accounts both the transmitted and received wave ellipticities (χ_t, χ_r) and the orientation angles (ψ_t, ψ_r). In this decomposition, S denotes the Stokes vector and Ω is the polarized power fraction. However, it may be noted that the S − Ω decomposition intrinsically ignores dominance in the target scattering mechanism while calculating the powers. In this work, improvement is proposed for the S − Ω decomposition by utilizing the degree of dominance in the scattering mechanism. The improved S − Ω (named as iS − Ω) decomposition powers are first compared with the existing m − χ and S − Ω powers for elementary (viz., trihedral and dihedral corner reflectors) and distributed targets using simulated CP-SAR data from quad-pol RADARSAT-2 data. An increase of ∼2% for odd and even-bounce powers obtained from the iS − Ω decomposition is observed for the trihedral and dihedral corner reflectors respectively. The analysis of the scattering powers for distributed targets shows that an increase of 15% and 12% in the even and odd-bounce powers is observed from iS − Ω for urban and bare soil areas respectively as compared to the m − χ and S − Ω decompositions. Besides, temporal variations in the scattering powers obtained from the iS − Ω decomposition are also analyzed for rice, cotton, and sugarcane crops at different growth stages.

随着SAR系统朝着业务应用的快速发展，使用紧凑型合成孔径雷达（CP-SAR）数据进行作物表征是最重要的。值得注意的是，作为双极化和四极化SAR系统之间的良好折衷，CP-SAR在更大的扫描范围和更低的数据速率方面具有优势。的米 -  χ CP分解考虑两个出了三个斯托克斯参数子的：（偏振度米），椭圆（χ）和取向角（ψ）来描述准单色部分偏振波的极化部分。建议在S中提高散射能力 - Ω分解，它考虑到帐户都发射和接收的波椭圆率（χ_吨，χ _{- [R} ）和取向角（ψ_吨，ψ _[R ）。在该分解中，S表示斯托克斯矢量，并且Ω是极化功率分数。但是，应该注意的是，S  -Ω分解在计算功率时会本质上忽略目标散射机制中的优势。在这项工作中， 通过利用散射机制中的优势程度，提出了S -Ω分解的改进方案。改进后的S  −Ω（称为iS 首先 ，使用来自四极点RADARSAT-2数据的模拟CP-SAR数据，将分解功率与基本（即三面和二面角反射器）和分布式目标的现有m  -  χ和S -Ω功率进行比较。从 三面角反射器和二面角拐角反射器分别观察到，从iS -Ω分解获得的奇数和偶数反射功率增加了约2％。对分布式目标的散射功率的分析表明， 与m  -  χ和S相比，城市和裸露土壤区域的iS -Ω分别观察到了偶数和奇数反弹力的15％和12％的增长。 −Ω分解。此外， 还分析了从iS -Ω分解获得的散射功率随时间的变化，分析了水稻，棉花和甘蔗作物在不同生长阶段的情况。