New Prediction for Extended Targets With Random Matrices
2014 (English)In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, Vol. 50, no 2, 1577-1589 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2014. Vol. 50, no 2, 1577-1589 p.
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:liu:diva-112656DOI: 10.1109/TAES.2014.120211ISI: 000344364500059OAI: oai:DiVA.org:liu-112656DiVA: diva2:768898
Funding Agencies|Linnaeus research environment CADICS - Swedish Research Council; frame project grant Extended Target Tracking - Swedish Research Council [621-2010-4301]; Collaborative Unmanned Aircraft Systems (CUAS) - Swedish Foundation for Strategic Research (SSF)2014-12-052014-12-052014-12-09