Gugliuzza, F., Bruno, A., Ardizzone, E. and Pirrone, R., 2019. An Effective Satellite Remote Sensing Tool Combining Hardware and Software Solutions. Communications in Computer and Information Science, 1074, 151 - 175.
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DOI: 10.1007/978-3-030-30110-1_9
Abstract
In this paper we propose a new effective remote sensing tool combining hardware and software solutions as an extension of our previous work. In greater detail the tool consists of a low cost receiver subsystem for public weather satellites and a signal and image processing module for several tasks such as signal and image enhancement, image reconstruction and cloud detection. Our solution allows to manage data from satellites effectively with low cost components and portable software solutions. We aim at sampling and processing of the modulated signal entirely in software enabled by Software Defined Radios (SDR) and CPU computational speed overcoming hardware limitation such as high receiver noise and low ADC resolution. Since we want to extend our previous method to demodulate signals coming from various meteorological satellites, we propose a new high frequency receiving system designed to receive and demodulate signals transmitted at 1.7 GHz. The signals coming from satellites are demodulated, synchronized and enhanced by using low level image processing techniques, then cloud detection is performed by using the well known K-means clustering algorithm. The hardware and software architecture extensions make our solution able to receive and demodulate high frequency and bandwidth meteorological satellite signals, such as those transmitted by NOAA POES, NOAA GOES, EUMETSAT Metop, Meteor-M and FengYun.
Item Type: | Article |
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ISSN: | 1865-0929 |
Additional Information: | Proceedings of 6th International Conference, SENSORNETS 2017, Porto, Portugal, February 19-21, 2017, and 7th International Conference, SENSORNETS 2018, Funchal, Madeira, Portugal, January 22-24, 2018. Revised Selected Papers |
Uncontrolled Keywords: | Remote sensing, satellite communication, signal processing,cloud detection |
Group: | Faculty of Media & Communication |
ID Code: | 34238 |
Deposited By: | Symplectic RT2 |
Deposited On: | 07 Jul 2020 08:54 |
Last Modified: | 14 Mar 2022 14:23 |
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