Search results for "KALMAN FILTERS"
showing 7 items of 7 documents
Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using In Situ Measurements
2017
International audience; The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil m…
Improved GNSS positioning exploiting a vehicular P2P infrastructure
2010
This paper considers the possibility to exploit external altitude measurements to improve the performance of a Kalman based GNSS receiver. The altitude measurements are provided by means of a peer to peer network, that is supposed to be based on the evolution of the 802.11 standard for the vehicular environment, namely the WAVE (802.11p). The performance of such a system are investigated for different characteristics of the aiding measurement and for a different number and disposals of the aiding peers. The aiding measurement is obtained starting from the altitude measurements that the other peers in the network send to the aided user. The experiments highlight the need for a parameter that…
Iterative altitude-aiding algorithm for improved GNSS positioning
2011
The system proposed in this study relies on a WAVE P2P network, which is a proper standard to fit the vehicular environment wireless communications requests. Starting from the chance to exchange information given by this infrastructure, the possibility to improve the performance of a global navigation satellite system (GNSS) receiver based on a Kalman filter is considered. This improvement is obtained exploiting the external altitude measurements provided by other peers in the network, equipped with GNSS receivers. The topic of an altitude-aided system has been described in a previous work, that highlighted the need for a parameter that points out the effectiveness and the consistency of th…
KALMAN FILTERS FOR GNSS APPLICATIONS
2011
Online Edge Flow Imputation on Networks
2022
Author's accepted manuscript © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. An online algorithm for missing data imputation for networks with signals defined on the edges is presented. Leveraging the prior knowledge intrinsic to real-world networks, we propose a bi-level optimization scheme that exploits the causal dependencies and the flow conservation, respe…
State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter
2008
An Extended Kalman Filter is designed in order to estimate both state variables and wind velocity vector at the same time for a non conventional unmanned aircraft. The proposed observer uses few measurements, obtained by means of either conventional simple air data sensors or a low cost GPS. To cope with the low rate of the GPS with respect to the other sensors, the EKF algorithm has been modified to allow for a dual rate measurement model. State propagation is obtained by means of an accurate six degrees of freedom nonlinear model of the aircraft dynamics. To obtain joint estimation of state and disturbance, wind velocity components are included in the set of the state variables. Both stoc…