5 research outputs found
Meta-optimization of the Extended Kalman filter's parameters through the use of the Bias-Variance Equilibrium Point criterion
The extraction of information on land cover classes
using unsupervised methods has always been of relevance to the
remote sensing community. In this paper, a novel criterion is proposed,
which extracts the inherent information in an unsupervised
fashion from a time series. The criterion is used to fit a parametric
model to a time series, derive the corresponding covariance matrices
of the parameters for the model, and estimate the additive noise
on the time series. The proposed criterion uses both spatial and
temporal information when estimating the covariance matrices
and can be extended to incorporate spectral information. The
algorithm used to estimate the parameters for the model is the
extended Kalman filter (EKF). An unsupervised search algorithm,
specifically designed for this criterion, is proposed in conjunction
with the criterion that is used to rapidly and efficiently estimate the
variables. The search algorithm attempts to satisfy the criterion by
employing density adaptation to the current candidate system. The
application in this paper is the use of an EKF to model Moderate
Resolution Imaging Spectroradiometer time series with a triply
modulated cosine function as the underlying model. The results
show that the criterion improved the fit of the triply modulated
cosine function by an order of magnitude on the time series over
all seven spectral bands when compared with the other methods.
The state space variables derived from the EKF are then used for
both land cover classification and land cover change detection.
The method was evaluated in the Gauteng province of South
Africa where it was found to significantly improve on land cover
classification and change detection accuracies when compared
with other methods.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=36hb201
Über die GPS-basierte Bestimmung troposphärischer Laufzeitverzögerungen
One major problem of precise GPS data analysis is that of modeling wetdelays with high precision. All conventional models have to fail in this task due to the impossibility of modeling wet delays solely from surface measurements like temperature and relative humidity. Actually, the non-hydrostatic component of the tropospheric propagation delay is highly influenced by the distribution of water vapor in the lower troposphere which cannot be sufficiently predicted with sole help of surface measurements. A work-around is to include atmospheric parameters as additional unknowns in the analysis of GPS data from permanent monitor stations that turns out to improve the quality of position estimates. Moreover, knowledge of zenith wet delays allows to obtain a highly interesting value for climatology and meteorology: integrated or precipitable water vapor being important for the energy balance of the atmosphere and holds share of more than 60% of the natural greenhouse effect. GPS can thereby contribute to the improvement of climate models and weather forecasting. This work outlines the application of ground-based GPS to climate research and meteorology without omitting the fact that precise GPS positioning can also highly benefit from using numerical weather models for tropospheric delay determination for applications where GPS troposphere estimation is not possible, for example kinematic and rapid static surveys. In this sense, the technique of GPS-derived tropospheric delays is seen as mutually improving both disciplines, precise positioning as well as meteorology and climatology
Machine Learning
Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience
Aeronautical engineering: A continuing bibliography with indexes (supplement 202)
This bibliography lists 447 reports, articles and other documents introduced into the NASA scientific and technical information system in June 1986
Bibliography of Lewis Research Center technical publications announced in 1993
This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1993. All the publications were announced in the 1993 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses