Linear Gaussian Models in Target Tracking
This paper studies a unifying framework for linear Gaussian models used in target tracking. We propose a customized linear Gaussian methodology (Integrated Ornstein-Uhlenbeck in local horizontal dimensions and 2<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> order Ornetein-Uhlenbeck in local vertical dimension) for context exploitation in long-term target prediction. We illustrate this approach with targets known to exhibit bounded altitude excursions and discuss both its advantages and limitations.<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1,2</sup>
Authors
- Stefano Coraluppi (ORCID: https://orcid.org/0000-0003-0071-0654)
Institutions
- Systems and Technology Research (United States) (US)
Publication Details
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1109/aero63441.2025.11068191
- Primary Topic
- Target Tracking and Data Fusion in Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00