On Sequential Track Extraction within the PMHT Framework. (27th December 2007)

• Record Type: Journal Article
• Authors: Wieneke Wieneke, Monika Monika; Koch Koch, Wolfgang Wolfgang
• Other Names: Luginbuhl Luginbuhl T. T. Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2007-12-27
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/276914
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially PMHT is based on expectation-maximization for handling with association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. In particular, the problem of track extraction and deletion is apparently not yet satisfactorily solved within this framework. A sequential likelihood-ratio (LR) test for track extraction has been developed and integrated into the framework of traditional Bayesian multiple hypothesis tracking by Günter van Keuk in 1998. As PMHT is a multiscan approach as well, it also has the potential for track extraction. In this paper, an analogous integration of a sequential LR test into the PMHT framework is proposed. We present an LR formula for track extraction and deletion using the PMHT update formulae. The LR is thus a by-product of the PMHT iteration process, as PMHT provides all required ingredients for a sequential LR calculation. Therefore, the resulting update formula for the sequential LR test affords the development of track-before-detect algorithms for PMHT. The approach is illustrated by a simple example.