DocumentCode :
148887
Title :
Object tracking extensions for accurate recovery of rainfall maps using microwave sensor network
Author :
Liberman, Yoav
Author_Institution :
Sch. of Electr.-Eng., Tel Aviv Univ., Tel Aviv, Israel
fYear :
2014
fDate :
1-5 Sept. 2014
Firstpage :
1322
Lastpage :
1326
Abstract :
Recently, diverse methods have been proposed for faithful reconstruction of instantaneous rainfall maps by using received signal level (RSL) measurements from commercial microwave network (CMN), especially in dense networks. The main lacking of these methods is that the temporal properties of the rain field had not been considered, hence their accuracy might be limited. This paper presents a novel method for accurate spatio-temporal reconstruction of rainfall maps, derived from CMN, by using an extension to object tracking algorithms. An efficient coherency algorithm is used, which relates between sequential instantaneous rainfall maps. Then by using Kalman filter, the observed rain maps are predicted and corrected. When comparing the estimates to actual rain measurements, the performance improvement of the rainfall mapping is manifested, even when dealing with a rather sparse network, and low temporal resolution of the measurements. The method proposed here is not restricted to the application of accurate rainfall mapping.
Keywords :
Kalman filters; atmospheric techniques; geophysical signal processing; microwave detectors; object tracking; rain; signal reconstruction; CMN; Kalman filter; RSL; coherency algorithm; instantaneous rainfall map reconstruction; low temporal resolution; object tracking algorithms; object tracking extensions; rain field temporal property; rain measurements; rainfall map recovery; received signal level measurements; sequential instantaneous rainfall maps; sparse network; spatio-temporal reconstruction; Kalman filters; Mathematical model; Microwave measurement; Microwave theory and techniques; Object tracking; Radar; Rain; Estimation; Microwave Network; Object Tracking; Rainfall Mapping; Reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon
Type :
conf
Filename :
6952464
Link To Document :
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