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Automatica ◽  
2021 ◽  
Vol 131 ◽  
pp. 109741
Author(s):  
Laura Menini ◽  
Corrado Possieri ◽  
Antonio Tornambè

Automatica ◽  
2021 ◽  
Vol 129 ◽  
pp. 109573
Author(s):  
Antonino Sferlazza ◽  
Sophie Tarbouriech ◽  
Luca Zaccarian

Author(s):  
O. Hernández‐González ◽  
F. Ramírez‐Rasgado ◽  
C. M. Astorga‐Zaragoza ◽  
M. E. Guerrero‐Sánchez ◽  
G. Valencia‐Palomo ◽  
...  

2020 ◽  
Vol 177 ◽  
pp. 107749
Author(s):  
Elvin Isufi ◽  
Paolo Banelli ◽  
Paolo Di Lorenzo ◽  
Geert Leus
Keyword(s):  

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Jorge Arevalo ◽  
Xubin Zeng ◽  
Matej Durcik ◽  
Michael Sibayan ◽  
Luke Pangle ◽  
...  

Abstract Land-atmosphere interactions at different temporal and spatial scales are important for our understanding of the Earth system and its modeling. The Landscape Evolution Observatory (LEO) at Biosphere 2, managed by the University of Arizona, hosts three nearly identical artificial bare-soil hillslopes with dimensions of 11 × 30 m2 (1 m depth) in a controlled and highly monitored environment within three large greenhouses. These facilities provide a unique opportunity to explore these interactions. The dataset presented here is a subset of the measurements in each LEO’s hillslopes, from 1 July 2015 to 30 June 2019 every 15 minutes, consisting of temperature, water content and heat flux of the soil (at 5 cm depth) for 12 co-located points; temperature, relative humidity and wind speed above ground at 5 locations and 5 different heights ranging from 0.25 m to 9–10 m; 3D wind at 1 location; the four components of radiation at 2 locations; spatially aggregated precipitation rates, total subsurface discharge, and relative water storage; and the measurements from a weather station outside the greenhouses.


2020 ◽  
Vol 65 (5) ◽  
pp. 2200-2206 ◽  
Author(s):  
Tarek Ahmed-Ali ◽  
Emilia Fridman ◽  
Fouad Giri ◽  
Mohamed Kahelras ◽  
Francoise Lamnabhi-Lagarrigue ◽  
...  

2020 ◽  
Vol 53 (1-2) ◽  
pp. 250-261
Author(s):  
B Omkar Lakshmi Jagan ◽  
S Koteswara Rao

The aim of this paper is to evaluate the performance of different filtering algorithms in the presence of non-Gaussian noise environment for tracking underwater targets, using Doppler frequency and bearing measurements. The tracking using Doppler frequency and bearing measurements is popularly known as Doppler-bearing tracking. Here the measurements, that is, bearings and Doppler frequency, are considered to be corrupted with two types of non-Gaussian noises namely shot noise and Gaussian mixture noise. The non-Gaussian noise sampled measurements are assumed to be obtained (a) randomly throughout the process and (b) repeatedly at some particular time samples. The efficiency of these filters with the increase in non-Gaussian noise samples is discussed in this paper. The performance of filters is compared with that of Cramer-Rao Lower Bound. Doppler-bearing extended Kalman filter and Doppler-bearing unscented Kalman filter are chosen for this work.


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