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Uwe D. Hanebeck
Researcher at Karlsruhe Institute of Technology
Publications - 575
Citations - 9054
Uwe D. Hanebeck is an academic researcher from Karlsruhe Institute of Technology. The author has contributed to research in topics: Kalman filter & Gaussian. The author has an hindex of 39, co-authored 549 publications receiving 7977 citations. Previous affiliations of Uwe D. Hanebeck include Technische Universität München & IAR Systems.
Papers
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Proceedings ArticleDOI
Sequence-Based Stochastic Receding Horizon Control Using IMM Filtering and Value Function Approximation
TL;DR: This work addresses sequence-based stochastic receding horizon control over networks where application layer acknowledgments are issued from the plant side upon reception of control inputs and derives a tractable policy by approximating the non-convex value function by a set of coupled quadratic functions.
Proceedings ArticleDOI
Multivariate parametric density estimation based on the modified Cramér-von Mises distance
TL;DR: A novel distance-based density estimation method is proposed, which considers the overall density function in the goodness-of-fit, and good performance is shown in an experimental comparison to the Expectation Maximization algorithm for Gaussian mixture densities.
Proceedings ArticleDOI
Evaluation of tracking methods for maritime surveillance
TL;DR: Evaluation of several multi-target tracking methods based on simulated scenarios in the maritime domain considers variations of the Joint Integrated Probabilistic Data Association (JIPDA) algorithm, namely the Linear Multi-Target IPDA, Linear Joint IPda, and Markov Chain Monte Carlo Data Association.
Proceedings ArticleDOI
Robust model predictive control with least favorable measurements
TL;DR: A novel conservative closed-loop control approach that does not calculate the expected impact of all measurements, but solely considers the single future measurement that has the worst impact on the control objective.
Proceedings ArticleDOI
Sequence-Based Receding Horizon Control over Networks With Delays and Data Losses
TL;DR: An iterative algorithm is presented for the computation of the parameters of a linear receding horizon controller that does not assume separation a priori, taking the dual effect into account and is optimal in the sense that it minimizes an upper bound of the underlying quadratic cost function with respect to the control sequences.