Extremal optimization for sensor report pre-processing
<|reference_start|>Extremal optimization for sensor report pre-processing: We describe the recently introduced extremal optimization algorithm and apply it to target detection and association problems arising in pre-processing for multi-target tracking.   Here we consider the problem of pre-processing for multiple target tracking when the number of sensor reports received is very large and arrives in large bursts. In this case, it is sometimes necessary to pre-process reports before sending them to tracking modules in the fusion system. The pre-processing step associates reports to known tracks (or initializes new tracks for reports on objects that have not been seen before). It could also be used as a pre-process step before clustering, e.g., in order to test how many clusters to use.   The pre-processing is done by solving an approximate version of the original problem. In this approximation, not all pair-wise conflicts are calculated. The approximation relies on knowing how many such pair-wise conflicts that are necessary to compute. To determine this, results on phase-transitions occurring when coloring (or clustering) large random instances of a particular graph ensemble are used.<|reference_end|>
@article{svenson2004extremal,
    title={Extremal optimization for sensor report pre-processing},
    author={Pontus Svenson},
    journal={Proc SPIE Vol 5429, p 162-171 (2004)},
    year={2004},
    doi={10.1117/12.542027},
    archivePrefix={arXiv},
    eprint={cs/0411072},
    primaryClass={cs.AI}
}