Comparative Analysis on Performance Evaluation of Naval Minesweeping

DOI

10.2991/icmit-16.2016.62How to use a DOI?

Keywords

Markov process Bayesian estimation minesweeping probability remaining mine

Abstract

The estimation of number of remaining mines is an important basis for the performance evaluation of naval minesweeping, and the accuracy of the estimation is related to the mastery of prior information and the selection of evaluation model. In this paper, we build the evaluation models by employing Markov process and Bayesian estimation theory to estimate the number of remaining mines. Then simulation experiments based on the above models were carried out, using the operational data which come from prior information of the minefield and information of swept mines. The results show that the Bayesian estimation is more reliable than Markov process in the case of sufficient prior information.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huidong Lu
AU  - Xinqin Chen
AU  - Wei Zhang
AU  - Chang Shu
AU  - Xuanmin Li
AU  - Longteng Li
AU  - Chengwen Zhu
PY  - 2016/04
DA  - 2016/04
TI  - Comparative Analysis on Performance Evaluation of Naval Minesweeping
BT  - Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology
PB  - Atlantis Press
SP  - 354
EP  - 358
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmit-16.2016.62
DO  - 10.2991/icmit-16.2016.62
ID  - Lu2016/04
ER  -