The rise of the polarimetric Kalman filter: a bibliometric study on its growing significance

Abstract

This paper presents a comprehensive study on the evolution, applications, and impact of the Polarimetric Kalman Filter (PKF) in the fields of signal processing and remote sensing. By employing a methodological framework that integrates literature collection, screening and selection, bibliometric analysis, and synthesis, we aim to elucidate the PKF's contributions and potential research trajectories within its applications. Our findings highlight the PKF's significant role in enhancing data assimilation, improving predictive accuracy, and refining measurement techniques across various domains, particularly in meteorological research and environmental monitoring. The analysis reveals the interdisciplinary nature of PKF applications and its capability to merge theoretical advancements with practical implementations, underlining the importance of sophisticated signal processing algorithms in interpreting complex environmental data. The study also identifies emerging trends, such as the integration of PKF with machine learning and artificial intelligence, indicating future directions for research that promise to push the boundaries of current methodologies and applications. This paper underscores the PKF's pivotal role in advancing signal processing and remote sensing technologies, offering insights into its continuing development and the expanding scope of its applications.