Related papers: Validation of Kalman Filter alignment algorithm wi…
We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where…
Ensemble data assimilation methods such as the Ensemble Kalman Filter (EnKF) are a key component of probabilistic weather forecasting. They represent the uncertainty in the initial conditions by an ensemble which incorporates information…
The ensemble Kalman filter (EnKF) is a data assimilation technique that uses an ensemble of models, updated with data, to track the time evolution of a usually non-linear system. It does so by using an empirical approximation to the…
We examine cosmic ray rejection methodology on data collected from InSb and Si:As detectors. The application of an Up-the-Ramp sampling technique with cosmic ray identification and mitigation is the focus of this study. This technique is…
DESTINY+ is an upcoming JAXA Epsilon medium-class mission to flyby multiple asteroids including Phaethon. As an asteroid flyby observation instrument, a telescope mechanically capable of single-axis rotation, named TCAP, is mounted on the…
In this paper, we investigate the implementation of a Python code for a Kalman Filter using the Numpy package. A Kalman Filtering is carried out in two steps: Prediction and Update. Each step is investigated and coded as a function with…
We present a method of using classical wavelet based multiresolution analysis to separate scales in model and observations during data assimilation with the ensemble Kalman filter. In many applications, the underlying physics of a phenomena…
In this paper, a position and velocity estimation method for robotic manipulators which are affected by constant bounded disturbances is considered. The tracking control problem is formulated as a disturbance rejection problem, with all the…
The MARS scanner is designed for the x-ray spectroscopic study of samples with the aid of computer tomography methods. Computer tomography allows the reconstruction of slices of an investigated sample using a set of shadow projections…
The alignment procedure of the Silicon Microstrip Tracker, SMT, and the Central Fiber Tracker, CFT, is described. Alignment uncertainties and resulting systematic errors in physics analyses are addressed.
Track geometry monitoring is essential for maintaining the safety and efficiency of railway operations. While Track Recording Cars (TRCs) provide accurate measurements of track geometry indicators, their limited availability and high…
The Kalman filter (KF) and its variants are among the most celebrated algorithms in signal processing. These methods are used for state estimation of dynamic systems by relying on mathematical representations in the form of simple…
In this paper, we propose an novel implementation of a simultaneous localization and mapping (SLAM) system based on a monocular camera from an unmanned aerial vehicle (UAV) using Depth prediction performed with Capsule Networks (CapsNet),…
The ensemble Kalman filter (EnKF) is an efficient algorithm for many data assimilation problems. In certain circumstances, however, divergence of the EnKF might be spotted. In previous studies, the authors proposed an…
The alignment of tracking detectors is crucial for the physics programme at the LHC, especially for precision measurements like the W mass. The alignment of the ATLAS silicon tracking detectors with a total of 5832 modules poses an…
Weak-lensing mass-mapping algorithms, which reconstruct the convergence field from galaxy shear measurements, are crucial for extracting higher-order statistics to constrain cosmological parameters. However, only limited research has…
We present a new particle tracking software algorithm designed to accurately track the motion of low-contrast particles against a background with large variations in light levels. The method is based on a polynomial fit of the intensity…
Recent detector concepts at future linear or circular $e^- e^+$ colliders emphasize the benefits of time-of-flight measurements for particle identification of long-lived charged hadrons. That method relies on a precise estimation of the…
An algorithm for pose and motion estimation using corresponding features in images and a digital terrain map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as a global reference enables recovering the absolute…
The Kalman filter (KF) is an optimal linear state estimator for linear systems, and numerous extensions, including the extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF), have been developed for…