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  • Research Article
  • Open Access

On Sequential Track Extraction within the PMHT Framework

EURASIP Journal on Advances in Signal Processing20072008:276914

  • Received: 1 April 2007
  • Accepted: 8 October 2007
  • Published:


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.


  • Information Technology
  • Quantum Information
  • Main Motivation
  • Iteration Process
  • Multiple Target

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Authors’ Affiliations

FGAN-FKIE, Neuenahrer Strasse 20, Wachtberg, 53343, Germany