Random Set Methods Estimation of Multiple Extended Objects

Date

2014-06-01

Author

Granstrom, Karl
Lundquist, Christian
Gustafsson, Fredrik
Orguner, Umut

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Random set-based methods have provided a rigorous Bayesian framework and have been used extensively in the last decade for point object estimation. In this article, we emphasize that the same methodology offers an equally powerful approach to estimation of so-called extended objects, i.e., objects that result in multiple detections on the sensor side. Building upon the analogy between Bayesian state estimation of a single object and random finite set (RFS) estimation for multiple objects, we give a tutorial on random set methods with an emphasis on multiple-extended-object estimation. The capabilities are illustrated on a simple yet insightful real-life example with laser range data containing several occlusions.

Subject Keywords

Control and Systems Engineering, Electrical and Electronic Engineering, Computer Science Applications

URI

https://hdl.handle.net/11511/41826

Collections

Department of Electrical and Electronics Engineering, Article