摘要
针对多型水下航行器试后大容量、多类型、可视化的数据处理需求,采用自适应内存映射技术、试验数据对象抽象提取、多线程等关键技术,设计了一种水下航行器通用的数据处理软件,软件可快速高效地实现各系统关键参数的数据特征值可视化分析和航行器综合性能评估,结合人工判读生成当前航行任务的评估报告,最终评判水下航行器的航行姿态、声学、磁学等工作效果和性能指标;经实际应用,软件满足了多型水下航行器海量数据处理需求,实现了不同任务、不同系统、不同侧重点的弹道参数的特征值分析、联合缩放、对比分析等处理方法;该软件具有通用化程度高,可移植性强,运行稳定可靠等特点,缩短了数据处理软件的研制周期,提高了工作效率,工程实践效果良好。
For the requirements of large capacity,multiple types,visual data processing technology after test of multiple type underwater vehicles,the universal massive data processing software of underwater vehicles was designed through adopting the technology with self-adaptive memory mapping,abstracted object extraction of the test data,multi-threading and other key technologies.Data processing software,which can quickly and efficiently realize the data eigenvalue analysis of key parameters and the comprehensive performance evaluation of the underwater vehicle,combined with manual interpretation to generate the evaluation report of the current navigation task,and finally judge the navigation status,acoustics,and magnetics work effect and performance index of the underwater vehicle.Through practical application,the software meets the massive data processing requirements of multi-type underwater vehicles,and realizes the eigenvalue analysis,joint zooming,and comparative analysis of different missions,different systems,and different emphasis on ballistic parameters.The software has the characteristics of high generalization,strong portability,stable and reliable operation,etc.,which shortens the development cycle of data processing software,improves work efficiency,and has good engineering practice results.
作者
时慧晶
刘凤伟
陈亮
Shi Huijing;Liu Fengwei;Chen Liang(Kunming Shipborne Equipment Research&Test Center,CSCI,Kunming 650051,China;School of Information and Electrical Engineering,Hunan University of Science and Technology,Xiangtan 411201,China)
出处
《计算机测量与控制》
2020年第11期131-134,共4页
Computer Measurement &Control
关键词
水下航行器
对象抽象提取
内存映射
性能评估
数据处理
underwater vehicle
abstracted object extraction
memory mapping
performance evaluation
data process