Litcius/Paper detail

A Multichannel Data Fusion Method to Enhance the Spatial Resolution of Microwave Radiometer Measurements

Matteo Alparone, Ferdinando Nunziata, Claudio Estatico, Maurizio Migliaccio

2020IEEE Transactions on Geoscience and Remote Sensing17 citationsDOI

Abstract

In this study, a method to improve the reconstruction performance of antenna-pattern deconvolution based on the gradient iterative regularization scheme is proposed. The method exploits microwave measurements acquired by a multichannel radiometer to enhance their native spatial resolution. The proposed rationale consists of using the information carried on a high-frequency (finer spatial resolution) channel to ameliorate the spatial resolution of the lowest resolution radiometer channel. Experiments performed using both synthetic and real special sensor microwave/imager (SSM/I) radiometer data demonstrate that an enhanced spatial resolution 19.35-GHz channel can be obtained by ingesting in the algorithm information coming from 37.0-GHz channel. This multichannel spatial resolution method is also shown to outperform the conventional gradient-like regularization scheme in terms of both observation of smaller targets and reduction of ringings and fluctuations.

Topics & Concepts

Image resolutionDeconvolutionRemote sensingRadiometerMicrowave radiometerMicrowave imagingMicrowaveChannel (broadcasting)Computer scienceResolution (logic)AlgorithmGeologyArtificial intelligenceTelecommunicationsSoil Moisture and Remote SensingCryospheric studies and observationsPrecipitation Measurement and Analysis