27 April 2018 A clutter-agnostic generalized labeled multi-Bernoulli filter
Author Affiliations +
Abstract
The labeled random finite set (LRFS) theory of B.-T. Vo and B.-N. Vo is the first systematic, theoretically rigorous formulation of true multitarget tracking, and is the basis for the generalized labeled multi-Bernoulli (GLMB) filter (the first implementable and provably Bayes-optimal multitarget tracking algorithm). Like most multitarget trackers, the GLMB filter is based on the assumption that clutter statistics are known a priori. Recent research has introduced RFS filters that are "clutter-agnostic," in the sense that they can address unknown, dynamically evolving clutter. These filters were unlabeled, however. In this paper we devise a clutter-agnostic GLMB (CA-GLMB) filter, based on the Bernoulli clutter-generator concept.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ronald Mahler, Ronald Mahler, } "A clutter-agnostic generalized labeled multi-Bernoulli filter", Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 106460D (27 April 2018); doi: 10.1117/12.2305464; https://doi.org/10.1117/12.2305464
PROCEEDINGS
12 PAGES


SHARE
RELATED CONTENT

Performance bounds for track-before-detect target detection
Proceedings of SPIE (September 03 1998)
Comparison of a grid based filter to a Kalman filter...
Proceedings of SPIE (September 16 2011)
Multisource multitarget filtering: a unified approach
Proceedings of SPIE (September 03 1998)
IMM modeling for AEW applications
Proceedings of SPIE (November 26 2001)
Design of an adaptive passive collision warning system for UAVs
Proceedings of SPIE (September 04 2009)

Back to Top