observable field
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2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Julien Baerenzung ◽  
Matthias Holschneider ◽  
Johannes Wicht ◽  
Vincent Lesur ◽  
Sabrina Sanchez

Abstract We present a new model of the geomagnetic field spanning the last 20 years and called Kalmag. Deriving from the assimilation of CHAMP and Swarm vector field measurements, it separates the different contributions to the observable field through parameterized prior covariance matrices. To make the inverse problem numerically feasible, it has been sequentialized in time through the combination of a Kalman filter and a smoothing algorithm. The model provides reliable estimates of past, present and future mean fields and associated uncertainties. The version presented here is an update of our IGRF candidates; the amount of assimilated data has been doubled and the considered time window has been extended from [2000.5, 2019.74] to [2000.5, 2020.33].


2020 ◽  
Author(s):  
Julien Baerenzung ◽  
Matthias Holschneider ◽  
Johannes Wicht ◽  
Vincent Lesur ◽  
Sabrina Sanchez

Abstract We present a new model of the Geomagnetic field spanning the last 20 years and called Kalmag. Deriving from the assimilation of CHAMP and SWARM vector field measurements, it separates the different contributions to the observable field through parameterized prior covariance matrices. To make the inverse problem numerically feasible it has been sequentialized in time though the combination of a Kalman filter and a smoothing algorithm. The model provides reliable estimates of past, present and future mean fields and associated uncertainties. The version presented here is an update of our IGRF candidates, the amount of assimilated data has been doubled and the considered time window has been extended from [2000.5,2019.74] to [2000.5,2020.33].


2020 ◽  
Vol 68 (7) ◽  
pp. 5544-5555
Author(s):  
Andrea Neto ◽  
Arturo Fiorellini Bernardis ◽  
Diego Emer ◽  
Angelo Freni ◽  
Nuria Llombart
Keyword(s):  

2018 ◽  
Vol 66 (4) ◽  
pp. 1736-1746 ◽  
Author(s):  
Andrea Neto ◽  
Nuria Llombart ◽  
Angelo Freni
Keyword(s):  

Author(s):  
LIDIA RUIZ-RIPOLL ◽  
ANA RIVAS ◽  
INMACULADA GALLEGO ◽  
SANTOS SÁNCHEZ-CAMBRONERO ◽  
ROSA M. BARBA

This paper presents a methodology for the dynamic estimation of traffic flows on all links of a network from observable field data assuming the first-in-first-out (FIFO) hypothesis. The traffic flow intensities recorded at the exit of the scanned links are propagated to obtain the flow waves on unscanned links. For that, the model calculates the flow-cost functions through information registered with the plate scanning technique. The model also responds to the concern about the parameter quality of flow-cost functions to replicate the real traffic flow behaviour. It includes a new algorithm for the adjustment of the parameter values to link characteristics when its quality is questionable. For that, it is necessary the a priori study of the location of the scanning devices to identify all path flows and to measure travel times in all links. A synthetic network is used to illustrate the proposed method and to prove its usefulness and feasibility.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4215


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