Team for Research in
Ubiquitous Secure Technology

Citation
Songhwai Oh, Shankar Sastry. "An Efficient Algorithm for Tracking Multiple Maneuvering Targets". Proc. of the IEEE International Conference on Decision and Control, December, 2005.

Abstract
Tracking multiple maneuvering targets in a cluttered environment is a challenging problem. A combination of interacting multiple model (IMM) and joint probabilistic data association (JPDA) has been successfully applied to track multiple maneuvering targets. In IMM, the motion of a maneuvering target is approximated by a finite number of simple, distinct kinematic models. However, the exact computation of the combined approach has the time complexity which is exponential in the numbers of kinematic models and measurements. When applying JPDA and IMM, the numbers of targets and kinematic models are known, so we can design a tracking system suitable for the given numbers of targets and kinematic models. But the number of measurements is not known in advance, and it poses a serious problem in computing association probabilities in JPDA. Hence, for a large problem, we need to seek for an efficient approximation algorithm. In this paper, we present a randomized algorithm which finds approximations of association probabilities with good fidelity and prove that the time complexity of the algorithm is polynomial in the size of the problem.

Electronic downloads

• http://www.eecs.berkeley.edu/~sho/papers/cdc05_mcmcda_imm.pdf
• cdc05_mcmcda_imm.pdf · application/pdf · 489 kbytes

• HTML

  Songhwai Oh, Shankar Sastry. <a
  href="http://www.truststc.org/pubs/50.html" >An
  Efficient Algorithm for Tracking Multiple Maneuvering
  Targets</a>, Proc. of the IEEE International
  Conference on Decision and Control, December, 2005.

• Plain text

  Songhwai Oh, Shankar Sastry. "An Efficient Algorithm
  for Tracking Multiple Maneuvering Targets". Proc. of
  the IEEE International Conference on Decision and Control,
  December, 2005.

• BibTeX

  @inproceedings{OhSastry05_EfficientAlgorithmForTrackingMultipleManeuveringTargets,
      author = {Songhwai Oh and Shankar Sastry},
      title = {An Efficient Algorithm for Tracking Multiple
                Maneuvering Targets},
      booktitle = {Proc. of the IEEE International Conference on
                Decision and Control},
      month = {December},
      year = {2005},
      abstract = {Tracking multiple maneuvering targets in a
                cluttered environment is a challenging problem. A
                combination of interacting multiple model (IMM)
                and joint probabilistic data association (JPDA)
                has been successfully applied to track multiple
                maneuvering targets. In IMM, the motion of a
                maneuvering target is approximated by a finite
                number of simple, distinct kinematic models.
                However, the exact computation of the combined
                approach has the time complexity which is
                exponential in the numbers of kinematic models and
                measurements. When applying JPDA and IMM, the
                numbers of targets and kinematic models are known,
                so we can design a tracking system suitable for
                the given numbers of targets and kinematic models.
                But the number of measurements is not known in
                advance, and it poses a serious problem in
                computing association probabilities in JPDA.
                Hence, for a large problem, we need to seek for an
                efficient approximation algorithm. In this paper,
                we present a randomized algorithm which finds
                approximations of association probabilities with
                good fidelity and prove that the time complexity
                of the algorithm is polynomial in the size of the
                problem.},
      URL = {http://www.truststc.org/pubs/50.html}
  }
  

Posted by Songhwai Oh on 5 Apr 2006.
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