Multidimensional Assignment Problems Arising in Multitarget and Multisensor Tracking

  • Aubrey B. Poore
Part of the Combinatorial Optimization book series (COOP, volume 7)


The ever-increasing demand in surveillance is to produce highly accurate target and track identification and estimation in real-time, even for dense target scenarios and in regions of high track contention. The use of multiple sensors, through more varied information, has the potential to greatly enhance target identification and state estimation. For multitarget tracking, the processing of multiple scans all at once yields high track identification. However, to achieve this accurate state estimation and track identification, one must solve an NP-hard data association problem of partitioning observations into tracks and false alarms in real-time. Over the last ten years a new approach to the problem formulation based on multidimensional assignment problems and near optimal solution in real-time by Lagrangian relaxation has evolved and is proving to be superior to all other approaches. This work reviews the problem formulation and algorithms with some suggested future directions.


Assignment Problem Lagrangian Relaxation Data Association Tracking Problem Multi Target Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 2000

Authors and Affiliations

  • Aubrey B. Poore
    • 1
  1. 1.Department of MathematicsColorado State UniversityFort CollinsUSA

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