Maximum Likelihood Joint Tracking and Association in Strong Clutter : Massima somiglianza per il tracciamento dei giunti e associazioni in grosse differenze, in: International Journal of Advanced Robotic Systems

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Autor	Perlovsky, Leonid I.; Deming, Ross W.
Erschienen	InTech Open Access Publisher, 2013
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Kurzbeschreibung	We have developed a maximum likelihood formulation for a joint detection, tracking and association problem. An efficient non‐combinatorial algorithm for this problem is developed in case of strong clutter for radar data. By using an iterative procedure of the dynamic logic process “from vague‐to‐crisp” explained in the paper, the new tracker overcomes the combinatorial complexity of tracking in highly‐cluttered scenarios and results in an orders‐of‐magnitude improvement in signalto‐ clutter ratio.

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International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Erschienen: 2004

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International Journal of Advanced Robotic Systems

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DMG-Lib		https://www.dmg-lib.org/dmglib/handler?docum=32511009
Europeana		http://www.europeana.eu/portal/record/2020801/dmglib_handler_docum_32511009.html
PDF		Maximum Likelihood Joint Tracking and Association in Strong Clutter

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Univ. Cassino

http://webuser.unicas.it/weblarm/larmindex.htm

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Publikationsdatum		2013
Lizenzinformation		This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License

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Maximum Likelihood Joint Tracking and Association in Strong Clutter : Massima somiglianza per il tracciamento dei giunti e associazioni in grosse differenze, in: International Journal of Advanced Robotic Systems

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