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一种海上非作战目标实时清洗方法 被引量:1

A Real-Time Cleaning Method for Marine Non-Combat Targets
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摘要 在进行海上作战态势分析时,通常需要剔除目标海域内对态势分析影响较小的非作战目标,只保留参考价值较高、作战相关的目标航迹数据。现有的行为规律挖掘方法大多是基于聚类的思想,作用于非作战目标清洗问题时工作步骤较为复杂、效果较差。结合态势分析需求,基于相似重复记录检测的思想,通过定义多维度记录匹配相似度(multi-dimension record similarity,MDRS),提出了一种海上非作战目标实时清洗方法。通过对多维航迹数据的相似重复检测,实现对非作战目标的实时清洗。在仿真军事场景上进行实验分析,结果表明所提方法能够实时、有效地检测出海上非作战目标。 Objectives: It is usually necessary to eliminate non-combat targets for conducting marine combat situation analysis. Because non-combat targets have little impacts on situational analysis and the retained combat-correlated targets have high reference value. Most of the existing behavior mining methods, which are based on the idea of clustering, are complicated and ineffective in cleaning of non-combat targets.Methods: Therefore, this paper defines multi-dimension record similarity(MDRS) and proposes a real-time cleaning method for marine non-combat targets(MNCT-RTCM). The proposed method realizes the real-time cleaning of non-combat targets by similar duplicate record detection of multi-dimensional track data. Results: The experiments are carried out on simulated military scenarios, and the results are evaluated and analyzed by calculating the recall rate and the precision rate. Conclusions: The results show that the MNCT-RTCM method can effectively detect non-combat targets and achieve real-time cleaning of noncombat targets in the marine combat environment.
作者 林雪原 李雪腾 潘新龙 李敏波 陈祥光 LIN Xueyuan;LI Xueteng;PAN Xinlong;LI Minbo;CHEN Xiangguang(Department of Electrical and Electronic Engineering,Yantai Nanshan University,Yantai 265713,China;91827 Troops,Weihai 264200,China;Institute of Information Fusion,Naval Aviation University,Yantai 264001,China;Software School,Fudan University,Shanghai 200433,China)
出处 《武汉大学学报(信息科学版)》 EI CAS CSCD 北大核心 2021年第9期1378-1385,共8页 Geomatics and Information Science of Wuhan University
基金 国家自然科学基金(91538201,61671157) 烟台市“双百计划”人才项目(YT201803)。
关键词 态势分析 非作战目标 实时清洗 相似重复记录 situation analysis non-combat targets real-time cleaning similar duplicate record
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  • 1韩京宇,徐立臻,董逸生.一种大数据量的相似记录检测方法[J].计算机研究与发展,2005,42(12):2206-2212. 被引量:32
  • 2Aebi, D., Perrochon, L. Towards improving data quality. In: Sarda, N.L., ed. Proceedings of the International Conference on Information Systems and Management of Data. Delhi, 1993. 273~281. 被引量:1
  • 3Wang, R.Y., Kon, H.B., Madnick, S.E. Data quality requirements analysis and modeling. In: Proceedings of the 9th International Conference on Data Engineering. Vienna: IEEE Computer Society, 1993. 670~677. 被引量:1
  • 4Rahm, E., Do, H.H. Data cleaning: problems and current approaches. IEEE Data Engineering Bulletin, 2000,23(4):3~13. 被引量:1
  • 5Galhardas, H., Florescu, D., Shasha, D., et al. AJAX: an extensible data cleaning tool. In: Chen, W.D., Naughton, J.F., Bernstein, P.A., eds. Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data. Texas: ACM, 2000. 590. 被引量:1
  • 6Hernandez, M.A., Stolfo, S.J. Real-World data is dirty: data cleansing and the merge/purge problem. Data Mining and Knowledge Discovery, 1998,2(1):9~37. 被引量:1
  • 7Lee, M.L., Ling, T.W., Lu, H.J., et al. Cleansing data for mining and warehousing. In: Bench-Capon, T., Soda, G., Tjoa, A.M., eds. Database and Expert Systems Applications. Florence: Springer, 1999. 751~760. 被引量:1
  • 8Monge, A.E. Matching algorithm within a duplicate detection system. IEEE Data Engineering Bulletin, 2000,23(4):14~20. 被引量:1
  • 9Monge, A.E., Elkan, C. The field matching problem: algorithms and applications. In: Simoudis, E., Han, J.W., Fayyad, U., eds. Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. Oregon: AAAI Press, 1996. 267~270. 被引量:1
  • 10Savasere, A., Omiecinski, E., Navathe, S.B. An efficient algorithm for mining association rules in large databases. In: Dayal, U., Gray, P., Nishio, S., eds. Proceedings of the 21st International Conference on Very Large Data Bases. Zurich: Morgan Kaufmann, 1995. 432~444. 被引量:1

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