@inproceedings{970863adb0a14bd5a49c67d4e196bb41,
title = "Advanced targets association based on GPU computation of PHD function",
abstract = "The precise and quick association of targets is one of the main challenging tasks in the signal processing field of the Multistatic Radar System (MRS). The paper deals with target association techniques based on the computation of the Probability Hypothetic Density (PHD) Function. The Computation time makes solving the PHD a very demanding task. The speedup of a newly developed algorithm depends on vectorization and parallel processing techniques. This paper describes the comparison between the original and parallel version of the target association algorithm with the full set of input data (without any knowledge about the approximation of targets direction) and the comparison with the advanced target association algorithm using additional input information about the direction of the target. All algorithms are processed in the MATLAB environment and Microsoft Visual Studio-C. The comparison also includes Central Processor Unit (CPU) and Graphics Processor Unit (GPU) version of all algorithms.",
author = "Jan Pidanic and Tomas Shejbal and Zdenek Nemec and Heru Suhartanto",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Conference on Advanced Computer Science and Information Systems, ICACSIS 2015 ; Conference date: 10-10-2015 Through 11-10-2015",
year = "2016",
month = feb,
day = "19",
doi = "10.1109/ICACSIS.2015.7415197",
language = "English",
series = "ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "13--22",
booktitle = "ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings",
address = "United States",
}