New Prediction for Extended Targets With Random Matrices

Download

index.pdf

Date

2014-04-01

Author

Granstrom, Karl
Orguner, Umut

Metadata

Show full item record

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

Item Usage Stats

11
views

43
downloads

This paper presents a new prediction update for extended targets whose extensions are modeled as random matrices. The prediction is based on several minimizations of the Kullback-Leibler divergence (KL-div) and allows for a kinematic state dependent transformation of the target extension. The results show that the extension prediction is a significant improvement over the previous work carried out on the topic.

Subject Keywords

Electrical and Electronic Engineering, Aerospace Engineering

URI

https://hdl.handle.net/11511/40488

Journal

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS

DOI

https://doi.org/10.1109/taes.2014.120211

Collections

Department of Electrical and Electronics Engineering, Article

Citation Formats

K. Granstrom and U. Orguner, “New Prediction for Extended Targets With Random Matrices,” IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, vol. 50, no. 2, pp. 1577–1589, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40488.