From the 1 of 5 linked papers with an AI index.
5 papers
Two-Filter Adaptive Gaussian Mixture Smoothing for Nonlinear Systems
Benjamin Schneiderheinze, Andrea De Vittori, Keith A. LeGrand +1
The paper introduces a recursive Bayesian smoother that refines the results of an adaptive Gaussian‑mixture filter for nonlinear systems, improving estimation accuracy in space obj…
Covariance Square Root Second-Order Mapping
Keith A. LeGrand, Braden Hastings, Jackson Kulik
In recursive state estimation, numerical error can play a major role in an algorithm's overall performance and reliability. Roundoff errors due to finite precision arithmetic can v…
Unscented and Higher-Order Linear Covariance Fidelity Checks and Measures of Non-Gaussianity
Jackson Kulik, Braden Hastings, Keith A. LeGrand
Linear covariance (LinCov) techniques have gained widespread traction in the modeling of uncertainty, including in the preliminary study of spacecraft navigation performance. While…
Higher-Order Tensor-Based Deferral of Gaussian Splitting for Orbit Uncertainty Propagation
G. Andrew Siciliano, Keith A. LeGrand, Jackson Kulik
Accurate propagation of orbital uncertainty is essential for a range of applications within space domain awareness. Adaptive Gaussian mixture-based approaches offer tractable nonli…
Nonlinearity and Uncertainty Informed Moment-Matching Gaussian Mixture Splitting
Jackson Kulik, Keith A. LeGrand
Many problems in navigation and tracking require increasingly accurate characterizations of the evolution of uncertainty in nonlinear systems. Nonlinear uncertainty propagation app…