Skip to search formSkip to main contentSkip to account menu
Adaptive filtering and change detection
TLDR
This chapter discusses Signal Estimation, which automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and changing the values of coefficients in a model to facilitate change detection.
Marginalized particle filters for mixed linear/nonlinear state-space models
TLDR
The derivation of the details for the marginalized particle filter for a general nonlinear state-space model is derived and it is demonstrated that the complete high-dimensional system can be based on a particle filter using marginalization for all but three states.
View on IEEE
Statistical Sensor Fusion
TLDR
This book is to explain state of the art theory and algorithms into statistical sensor fusion, covering estimation, detection and non-linear filtering theory with applications to localisation, navigation and tracking problems.
Particle filters for positioning, navigation, and tracking
TLDR
The technique of map matching is used to match an aircraft's elevation profile to a digital elevation map and a car's horizontal driven path to a street map and it is shown that the accuracy is comparable with satellite navigation but with higher integrity.
View via Publisher
Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements
TLDR
The focus of this article is to illustrate the relation between performance requirements, such as those stated by the Federal Communications Commission (FCC), and the available measurements.
View on IEEE
Particle filter theory and practice with positioning applications
  • F. Gustafsson
  • Computer Science
    IEEE Aerospace and Electronic Systems Magazine
  • 12 August 2010
TLDR
This tutorial serves two purposes: to survey the part of the theory that is most important for applications and to survey a number of illustrative positioning applications from which conclusions relevant for the theory can be drawn.
View on IEEE
Positioning using time-difference of arrival measurements
TLDR
This work suggests and compares a Monte Carlo based method for positioning and a gradient search algorithm using a nonlinear least squares framework and has the feature of being easily extended to a dynamic framework where a motion model of the transmitter is included.
View on IEEE
Slip-based tire-road friction estimation
View via Publisher
Some Relations Between Extended and Unscented Kalman Filters
TLDR
It is shown that the sigma point function evaluations can be used in the classical EKF rather than an explicitly linearized model, and a less cited version of the EKf based on a second-order Taylor expansion is shown to be quite closely related to UKF.
View on IEEE
Mobile Positioning Using Wireless Networks
...
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License