Conference Agenda

Polarimetric Synthetic Aperture Radar (PolSAR) is highly effective for characterizing scattering targets, offering rich information about their physical and structural properties. Over the years, numerous decomposition techniques—both data-driven and model-based—have been developed to interpret PolSAR measurements and separate the contributions of different scattering mechanisms. Examples include model-based approaches such as Freeman–Durden and Yamaguchi decompositions.

However, a key limitation of most model based approaches lies in how the scattering components are extracted. The mathematical operations involved often fail to preserve the positive semi-definite (PSD) nature of the resulting covariance or coherency matrices. Since physical scattering matrices must remain PSD to ensure valid power, this issue can lead to non-physical or unstable results. To address this, various correction techniques could be applied as in Arii ANNED. Nevertheless, in some instances such adjustments may distort the original data or reduce interpretability, highlighting the need for decomposition strategies that naturally maintain the physical and statistical integrity of the polarimetric information.

In this study, we investigate and compare different strategies for decomposing a partial target into two distinct components: a primary (focus) partial target and a residual, physically feasible partial target. We call this 1F+R. Please note the Focus target we extract is partial and can have any entropy. Its covariance matrix is not forced to have rank 1. Specifically, we compared different extraction methods based on simple subtraction, inner product, Rayleigh quotient optimisations (RQO), vectorisation of the covariance matrix and notch filtering, and tensor fields decompositions. We checked these extraction methods evaluating which one preserves the total power and maintains the PSD property across both the Focus and Residual partial targets. Preserving these characteristics is crucial for ensuring that the decomposition remains meaningful and that each component accurately represents its corresponding scattering mechanism without introducing artifacts.

To test the mentioned methodologies, we performed extensive Monte Carlo simulations to test its accuracy under controlled conditions. Furthermore, we applied the same analysis to real quad-polarimetric datasets acquired from ALOS-2 and (soon to) BIOMASS missions. These experiments allow us to assess the algorithm’s performance on real-world data characterized by different target types and scattering conditions. The results confirm that not all extractions techniques preserve PSD and polarimetric characteristics and we come with final suggested procedures including stages like RQO or tensor field analysis to be considered.