Search results for "kriging"
showing 10 items of 93 documents
Distributed radio map reconstruction for 5G automotive
2018
Se espera que los mapas de entorno radio sean una herramienta esencial para la optimización y gestión de recursos del 5G en vehículos. En este trabajo, consideramos el problema de la reconstrucción del mapa de entorno radio utilizando una red de sensores inalámbricos formada por nodos sensores en vehículos, nodos de acceso de una infraestructura de ciudad inteligente, etc. Debido a las limitaciones de recursos en las redes de sensores, es crucial seleccionar un pequeño número de mediciones de los sensores para reconstruir el campo. En este contexto, presentamos un novedoso algoritmo distribuido basado en el método de regresión Kriging para la reconstrucción del mapa de entorno radio en térm…
A low complexity distributed cluster based algorithm for spatial prediction
2017
Los mapas del entorno radioeléctrico (REM) pueden ser una herramienta esencial para numerosas aplicaciones en las futuras redes inalámbricas 5G. En este trabajo, empleamos un popular método geoestadístico llamado kriging ordinario para estimar el REM de un área cubierta por un eNodeB equipado con múltiples antenas. Los sensores inalámbricos se distribuyen por el área de interés y se organizan clústeres adaptativos de sensores para mejorar la calidad de la estimación del canal. En este trabajo, modificamos el algoritmo de clustering distribuido propuesto en un trabajo anterior para reducir la complejidad de la predicción de kriging. Se realizan simulaciones para detallar la técnica de formac…
Distributed channel prediction for multi-agent systems
2017
Los sistemas multiagente (MAS) se comunican a través de una red inalámbrica para coordinar sus acciones e informar sobre el estado de su misión. La conectividad y el rendimiento del sistema pueden mejorarse mediante la predicción de la ganancia del canal. Presentamos un esquema basado en regresión de procesos gaussianos (GPR) distribuidos para predecir el canal inalámbrico en términos de la potencia recibida en el MAS. El esquema combina una máquina de comité bayesiano con un esquema de consenso medio, distribuyendo así no sólo la memoria sino también la carga computacional y de comunicación. A través de simulaciones de Monte Carlo, demostramos el rendimiento del GPR propuesto. RACHEL TEC20…
Mapping landscape canopy nitrogen content from space using PRISMA data
2021
Abstract Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently launched and upcoming science-driven missions, e.g. PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), respectively. Moreover, the high-priority mission candidate Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is expected to globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. Thanks to the provision of contiguous visible-to-shortwave infrared spectral data, hyperspectral missions open enhanced …
Improving spatial temperature estimates by resort to time autoregressive processes
2012
Temperature estimation methods usually involve regression followed by kriging of residuals (residual kriging). Despite the performance of such models, there is invariably a residual which is not necessarily unpredictable because it may still be correlated in time. We set out to analyse such residuals through resort to autoregressive processes. It is shown that the optimal period varies depending on whether it is identified by functions of the form resd = f(resd−1, resd−2, ..., resd−p) or by partial correlations. Autoregressive processes significantly improve estimates, which are evaluated by cross-validations. Finally, the two following points are discussed: (1) the assumptions of the autor…
Temperature interpolation by local information ; the example of France
2010
International audience; Methods of interpolation, whether based on regressions or on kriging, are global methods in which all the available data for a given study area are used. But the quality of results is affected when the study area is spatially very heterogeneous. To overcome this difficulty, a method of local interpolation is proposed and tested here with temperature in France. Starting from a set of weather stations spread across the country and digitized as 250 m-sided cells, the method consists in modelling local spatial variations in temperature by considering each point of the grid and the n weather stations that are its nearest neighbours. The procedure entails a series of steps…
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…
Spatiotemporal modeling and prediction of solar radiation
2003
[1] The radiation budget in the Earth-atmosphere system is what drives Earth's climate, and thus measurements of this balance are needed to improve our knowledge of Earth's climate and climate change. In the present paper we focus on the analysis of the surface shortwave radiation budget (SSRB), which is the amount of energy in the solar region of the electromagnetic spectrum (0.2–4.0 μm) absorbed at the surface. The SSRB has to be modeled from the surface to the top of the atmosphere, jointly with information about the state of the atmosphere and the surface. These data come from satellites orbiting the Earth and are often missing or disturbed. Its interest is not only at global scales; ra…
Seasonal precipitation interpolation at the Valencia region with multivariate methods using geographic and topographic information
2009
The spatial pattern of precipitation is a complex variable that strongly depends on other geographic and topographic factors. As precipitation is usually known only at certain locations, interpolation procedures are needed in order to predict this variable in other regions. The use of multivariate interpolation methods is usually preferred, as secondary variables—generally derived using GIS tools—correlated with precipitation can be included. In this paper, a comparative study on different univariate and multivariate interpolation methodologies is presented. Our study area is centred in the region of Valencia, located to the eastern Spanish Mediterranean coast. The followed methodology can …
Application of Radio Environment Map Reconstruction Techniques to Platoon-based Cellular V2X Communications
2020
Vehicle platoons involve groups of vehicles travelling together at a constant inter-vehicle distance, with different common benefits such as increasing road efficiency and fuel saving. Vehicle platooning requires highly reliable wireless communications to keep the group structure and carry out coordinated maneuvers in a safe manner. Focusing on infrastructure-assisted cellular vehicle to anything (V2X) communications, the amount of control information to be exchanged between each platoon vehicle and the base station is a critical factor affecting the communication latency. This paper exploits the particular structure and characteristics of platooning to decrease the control information exch…