Tropospheric polynomial coefficients for real-time regional correction by Kalman filtering from multisource data

Großer Beleg Real - Time Structure from Motion Using Kalman Filtering

Simultaneous localization and mapping (SLAM) is one of the core problems in robotics. Its central theme is the estimation of the location and motion of a mobile robot situated in an unknown environment and the simultaneous construction of a map of this environment. In this work, the problem is tackled by using vision sensors. Therefore, classical Structure From Motion (SFM) techniques, which ha...

14.9 Real-time Merging of Multisource Data

We describe an extension of the virtual volume concept to multiple sensors. Data from multiple sensors are combined in real-time and mapped into a constantly updating three-dimensional grid. The data are combined in a time-centric manner, with data replacing older data, regardless of the sensor that the older data came from. We discuss scaling problems with this method and how they can be resol...

Real-Time Kalman Filtering for Nonuniformity Correction in Infrared Focal-Plane Arrays∗

A new algorithm for nonuniformity correction in infrared focal-plane arrays has been developed. The method is based on Kalman Filter theory. The algorithm operates, per pixel and per frame, assuming that the nonuniformity parameters follow a Gauss-Markov model. The uncertainty on the input irradiance parameter of the observation model is solved using the spatial infrared information collected f...

Kalman filtering for disease-state estimation from microarray data

MOTIVATION In this paper, we propose using the Kalman filter (KF) as a pre-processing step in microarray-based molecular diagnosis. Incorporating the expression covariance between genes is important in such classification problems, since this represents the functional relationships that govern tissue state. Failing to fulfil such requirements may result in biologically implausible class predict...

Extended Kalman Filtering by