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Filtration And Enhancement Of Environmental Characteristics Extracted From Sar Imagery Using Dynamic Kalman Technique, Ivan E. Villalon-Turrubiates
Filtration And Enhancement Of Environmental Characteristics Extracted From Sar Imagery Using Dynamic Kalman Technique, Ivan E. Villalon-Turrubiates
Iván Esteban Villalón Turrubiates
In this study, we propose a new computational paradigm based on the use of the Kalman filtering technique adjusted to reconstruct the dynamic behavior of the physical and electrical characteristics of different environmental monitoring data provided via reconstructive SAR imagery. As a matter of particular study we develop and report the Kalman filter-based algorithm for high-resolution filtration of the dynamic behavior of the hydrological indexes of the particular real-world SAR images of the test remotely sensed scenes. The simulation results verify the efficiency of the proposed approach.
Simulation Study Of The Unified Bayesian-Regularization Technique For Enhanced Radar Imaging, Yuriy V. Shkvarko, Ivan E. Villalon-Turrubiates
Simulation Study Of The Unified Bayesian-Regularization Technique For Enhanced Radar Imaging, Yuriy V. Shkvarko, Ivan E. Villalon-Turrubiates
Iván Esteban Villalón Turrubiates
In this paper, we intend to present the results of extended simulation study of the family of the radar image (RI) formation algorithms that employ the recently developed and investigated fused Bayesian-regularization (FBR) paradigm for high-resolution reconstruction of the spatial spectrum pattern (SSP) of the wavefield sources distributed in the remotely sensed environment. The FBR methodology is based on the aggregation of the Bayesian minimum risk statistical optimal estimation strategy with the descriptive weighted constrained least squares optimization technique that involves the non trivial a priori information on the desired properties of the SSP to be reconstructed from the actually …