Abstract
The problem of tracking a reentry ballistic object by processing radar measurements is considered in the paper. Sequential Monte Carlo-based filter is proposed for dealing with high nonlinearity of the object dynamics. A multiple model configuration is incorporated into the algorithm for overcoming the uncertainty about the object ballistic characteristics. The performance of the suggested multiple model particle filter (PF) is evaluated by Monte Carlo simulation.
Research Supported in part by Center of Excellence BIS21 grant ICA1-2000-70016, an European Community Marie Curie Fellowship and in the framework of the Control Training Site, and by Bulgarian Foundation for Scientific Investigations grants I-1202/02 and I-1205/02.
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Angelova, D., Simeonova, I., Semerdjiev, T. (2004). Monte Carlo Algorithm for Ballistic Object Tracking with Uncertain Drag Parameter. In: Lirkov, I., Margenov, S., Waśniewski, J., Yalamov, P. (eds) Large-Scale Scientific Computing. LSSC 2003. Lecture Notes in Computer Science, vol 2907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24588-9_11
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DOI: https://doi.org/10.1007/978-3-540-24588-9_11
Publisher Name: Springer, Berlin, Heidelberg
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