参数自适应动态贝叶斯舰船态势估计算法

doi:10.19665/j.issn1001-2400.2019.02.026

西安电子科技大学学报 ›› 2019, Vol. 46 ›› Issue (2): 158-163.doi: 10.19665/j.issn1001-2400.2019.02.026

参数自适应动态贝叶斯舰船态势估计算法

毕城¹,王玲琳²,刘永信¹()

^1. 内蒙古大学电子信息工程学院,内蒙古自治区呼和浩特 010021
^2. 内蒙古大学计算机学院,内蒙古自治区呼和浩特 010021

收稿日期:2018-11-19 出版日期:2019-04-20 发布日期:2019-04-20
通讯作者: 刘永信
作者简介:毕城(1995-),男,内蒙古大学硕士研究生. E-mail: bicheng_yt@163.com
基金资助:
国家重点研究发展计划(2017YFC1405204);国家重点研究发展计划(2017YFC1405601);国家自然科学基金(61362002);国家自然科学基金(61701263)

Algorithm for the assessment of ship situation based on the parameter adaptive dynamic Bayesian network

BI Cheng¹,WANG Linglin²,LIU Yongxin¹()

^1. College of Electronic Information Engineering, Inner Mongolia Univ., Hohhot 010021, China
^2. College of Computer Science, Inner Mongolia Univ., Hohhot 010021, China

Received:2018-11-19 Online:2019-04-20 Published:2019-04-20
Contact: Yongxin LIU

摘要/Abstract

摘要：

为减少动态海域下贝叶斯网络舰船态势估计算法较大的误差,提出了一种改进的动态贝叶斯网络舰船态势估计算法。该算法根据多路传感器的数据和新获取的态势信息进行推理,通过计算新态势要素与原有态势要素间的互信息构建并更新动态贝叶斯网络参数。与传统贝叶斯网络态势估计算法对比,在仿真情况下对10000艘舰船进行合作态势估计,改进动态贝叶斯网络的舰船态势估计算法合作舰船错误率降低了7.1%;用实测数据,目标的合作态势提升了4.2%。改进的算法不仅能够实时地反映舰船环境变化,同时还提高了目标态势估计的准确概率,为海监提供了一种舰船态势分析与决策的技术支持。

关键词: 信息融合, 态势估计, 舰船目标, 动态贝叶斯网络, 数据分析

Abstract:

In order to reduce the error of the Bayesian network algorithm for the assessment of ship situation in the dynamic area of the ocean, an improved algorithm for the assessment of the ship situation is proposed based on the dynamic Bayesian network. The algorithm makes an inference based on the data from multiple sensors and newly acquired situation information. By calculating the mutual information between new situational elements and original situational elements, the dynamic Bayesian network parameters are constructed and updated. Compared with the model of the traditional Bayesian Network, the error rate of the cooperative target of the ship reduces by 7.1% through simulation of about 10,000 ships. By using the improved dynamic Bayesian network algorithm for the assessment of ship situation, under the measured data, the cooperation of situation for the target has increased by 4.2%. The algorithm proposed in this paper not only reflects the environment of ship changes in real time, but also improves the accuracy of the target situation, thus providing a technical support for analysis and decision-making of the situation of ships for Marine Surveillance.

Key words: information fusion, situation assessment, ship target, dynamic Bayesian network, data analysis

中图分类号:

TP186

毕城,王玲琳,刘永信. 参数自适应动态贝叶斯舰船态势估计算法[J]. 西安电子科技大学学报, 2019, 46(2): 158-163.

BI Cheng,WANG Linglin,LIU Yongxin. Algorithm for the assessment of ship situation based on the parameter adaptive dynamic Bayesian network[J]. Journal of Xidian University, 2019, 46(2): 158-163.

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目标时刻	合作船只数量
目标时刻	DBN算法	文中算法
t₁	4210	4210
t₂	2951	3543
t₄	3412	3712

目标时刻	合作态势推理概率
目标时刻	DBN算法	文中算法
t₁	0.6234	0.6234
t₂	0.5633	0.6044
t₄	0.5808	0.6222

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参数自适应动态贝叶斯舰船态势估计算法

Algorithm for the assessment of ship situation based on the parameter adaptive dynamic Bayesian network

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