Search results for "Kalman filter"
showing 10 items of 108 documents
JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES
2018
In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By leveraging the Kalman filter framework, a three steps iterative algorithm is utilized to predict and update signal estimation as well as graph topology learning, called Topological Kalman Filter or TKF. Similar to the regular Kalman filter, we first predict the a posterior signal state based on the prior available data and then this prediction is updated and corrected based on the recently arrived measurement. But contrary to the conventional Kalman filter algorithm, we have no information of the transition matrix and hence we relate t…
Wind component estimation for UAS flying in turbulent air
2019
One of the most important problem of autonomous flight for UAS is the wind identification, especially for small scale vehicles. This research focusses on an identification methodology based on the Extended Kalman Filter (EKF). In particular authors focus their attention on.the filter tuning problem. The proposed procedure requires low computational power, so it is very useful for UAS. Besides it allows a robust wind component identification even when, as it is usually, the measurement data set is affected by noticeable noises. (C) 2019 Elsevier Masson SAS. All rights reserved.
Performance Estimation using the Fitness-Fatigue Model with Kalman Filter Feedback
2016
Abstract Tracking and predicting the performance of athletes is of great interest, not only in training science but also, increasingly, for serious hobbyists. The increasing availability and use of smart watches and fitness trackers means that abundant data is becoming available, and the interest to optimally use this data for performance tracking and training optimization is great. One competitive model in this domain is the 3-time-constant fitness-fatigue model by Busso based on the model by Banister and colleagues. In the following, we will show that this model can be written equivalently as a linear, time-variant state-space model. With this understanding, it becomes clear that all meth…
Tracking of blood vessels motion from 4D-flow MRI data
2022
This paper presents a novel approach to track objects from 4D Flow MRI data. A salient feature of the proposed method is that it fully exploits the geometrical and dynamical nature of the information provided by this imaging modality. The underlying idea consists in formulating the tracking problem as a data assimilation problem, in which both position and velocity observations are extracted from the 4D Flow MRI data series. Optimal estate estimation is then performed in a sequential fashion via Kalman filtering. The capabilities of the method are extensively assessed in a numerical study involving synthetic and clinical data.
Optimal Flight Path Determination in Turbulent Air: A Modified EKF Approach
2018
By using the Extended Kalman Filter an accurate path following in turbulent air is performed. The procedure employs simultaneously two dierent EKFs: the rst one estimates disturbances, the second one aords to determine the necessary controls displacements for rejecting those ones. To tune the EKFs an optimization algorithm has been designed to automatically determine Process Noise Covariance and Measurement Noise Covariance matrices. The rst lter, by using instrumental measurements gathered in turbulent air, estimates wind components. The second one obtains command laws able to follow the desired ight path. To perform this task aerodynamic coecients have been modied. Such a procedure leads …
AN EXTENDED KALMAN FILTER BASED TECHNIQUE FOR ON-LINE IDENTIFICATION OF UAS PARAMETERS.
2015
The present article deals with the identification,at the same time, of aircraft stability and control parameters taking into account dynamic damping derivatives. Such derivatives,due to the rate of change of the angle of attack, are usually neglected. So the damping characteristics of aircraft dynamics are attributed only on pitch rate derivatives. To cope with the dynamic effects of these derivatives, authors developed devoted procedures to estimate them. In the present paper, a complete model of aerodynamic coefficients has been tuned-up to identify simultaneously the whole set of derivatives. Besides, in spite of the employed reduced order model and/or decoupled dynamics, a six degrees o…
An Extended Kalman Filter-Based Technique for On-Line Identification of Unmanned Aerial System Parameters
2015
ABSTRACT: The present article deals with the identification, at the same time, of aircraft stability and control parameters taking into account dynamic damping derivatives. Such derivatives, due to the rate of change of the angle of attack, are usually neglected. So the damping characteristics of aircraft dynamics are attributed only on pitch rate derivatives. To cope with the dynamic effects of these derivatives, authors developed devoted procedures to estimate them. In the present paper, a complete model of aerodynamic coefficients has been tuned-up to identify simultaneously the whole set of derivatives. Besides, in spite of the employed reduced order model and/or decoupled dynamics, a s…
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…
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…
A distributed detection and prevention scheme from malicious nodes in vehicular networks
2016
Summary Vehicular environments still remain vulnerable to various potential attacks because of continuous interactions and information exchange between vehicles despite the deployment of authentication techniques by communication standards. Therefore, an authenticated node with a certificate could initiate an attack while complying with implemented protocols. Some mechanisms were proposed to enhance communication technologies, but none of them was able to anticipate nodes' behavior. They also mismanage oscillating vehicles, because they evict them automatically after misbehaving. In this paper, we propose a preventive mechanism, namely, Intrusion Prevention and Detection System (IPDS), able…