A Model-Free Four Component Scattering Power Decomposition for Polarimetric SAR Data

Target decomposition methods from polarimetric Synthetic Aperture Radar (PolSAR) data provides target scattering information. In this regard, several conventional model-based use power components to analyze SAR data. However, the typical hierarchical process enumerate uses various branching conditions, leading limitations. These techniques assume ad hoc models within a radar resolution cell. Therefore, of makes computation powers ambiguous. Some common issues decompositions are related compensation orientation angle about line sight and occurrence negative components. We propose model-free four-component that alleviates these issues. proposed approach, we nonconventional 3-D Barakat degree polarization obtain state scattered electromagnetic wave. The is used even-bounce, odd-bounce, diffused Along with this, measure asymmetry also proposed, which then suitably utilized helicity power. All roll-invariant, nonnegative, unambiguous. addition an unsupervised clustering technique preserves dominance for different targets. This assists in understanding importance diverse mechanisms based on characteristics. adequately captures clusters’ variations one another according their physical geometrical properties. study, L -, C X -band full-polarimetric three datasets show effectiveness natural interpretability results. code available at:  https://github.com/Subho07/MF4CF