DocumentCode
567445
Title
Generalized PHD filters via a general chain rule
Author
Clark, Daniel ; Mahler, Ronald
Author_Institution
Dept. of Electr., Electron. & Comput. Eng., Heriot-Watt Univ., Edinburgh, UK
fYear
2012
fDate
9-12 July 2012
Firstpage
157
Lastpage
164
Abstract
This paper introduces a general chain rule (GCR) for Gâteaux differentials/Gâteaux derivatives, and describes its consequences for multitarget detection and tracking. After describing the GCR and its specific form for functionals and functional derivatives, we use it to derive two new PHD filters: (1) a PHD filter for general models of target-generated measurements with general clutter processes; and (2) a multisensor version of this filter.
Keywords
clutter; filtering theory; object detection; sensor fusion; target tracking; GCR; Gâteaux differentials-Gâteaux derivatives; clutter processes; general chain rule; generalized PHD filters; multisensor version; multitarget detection; multitarget tracking; target-generated measurements; Approximation methods; Clutter; Current measurement; Equations; Filtering theory; Mathematical model; Target tracking; Gâteaux derivative; PHD filter; chain rule; finite-set statistics; functional derivative; random sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion (FUSION), 2012 15th International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4673-0417-7
Electronic_ISBN
978-0-9824438-4-2
Type
conf
Filename
6289800
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