most citedTrack-To-Track Association for Fusion of Dimension-Reduced Estimates

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eess.SP2024

Broadband Passive Sonar Track-Before-Detect Using Raw Acoustic Data

Daniel Bossér, Magnus Lundberg Nordenvaad, Gustaf Hendeby +1

This article concerns the challenge of reliable broadband passive sonar target detection and tracking in complex acoustic environments. Addressing this challenge is becoming increa…

eess.SP20241 cited

Adaptive Basis Function Selection for Computationally Efficient Predictions

Anton Kullberg, Frida Viset, Isaac Skog +1

Basis Function (BF) expansions are a cornerstone of any engineer's toolbox for computational function approximation which shares connections with both neural networks and Gaussian…

eess.SP2024

Joint State and Parameter Estimation Using the Partial Errors-in-Variables Principle

Peng Liu, Kailai Li, Gustaf Hendeby +1

This letter proposes a new method for joint state and parameter estimation in uncertain dynamical systems. We exploit the partial errors-in-variables (PEIV) principle and formulate…

eess.SP2023

Unified Linearization-based Nonlinear Filtering

Anton Kullberg, Isaac Skog, Gustaf Hendeby

This letter shows that the following three classes of recursive state estimation filters: standard filters, such as the extended Kalman filter; iterated filters, such as the iterat…

eess.SP2023

On the Relationship Between Iterated Statistical Linearization and Quasi-Newton Methods

Anton Kullberg, Martin A. Skoglund, Isaac Skog +1

This letter investigates relationships between iterated filtering algorithms based on statistical linearization, such as the iterated unscented Kalman filter (IUKF), and filtering…

eess.SP20231 cited

Track-To-Track Association for Fusion of Dimension-Reduced Estimates

Robin Forsling, Zoran Sjanic, Fredrik Gustafsson +1

Network-centric multitarget tracking under communication constraints is considered, where dimension-reduced track estimates are exchanged. Previous work on target tracking in this…