摘要
针对惯性测试样本数据具有灰色、贫信息性质,提出了采用测量加权融合的方法处理当前样本与历史样本关系,以灰色系统理论的GM(1,1)模型求解标准差,以"随机区间数可能度"取代"点值"为评价指标,合理地解决了惯组稳定性分析中,贫信息、灰色性质所导致评价结论可靠性低的问题,有效地增强了评价结论的稳健性,为仪器设备延寿、贮存环境影响分析等提供了有效的数据处理方法。
In this paper,in view of the grey and poor information nature of the inertial test sample data,a method of weighted dispersion fusion is proposed to deal with the relationship between the current sample and the historical sample.The introduction of GM(1,1)model was used to calculate the sample standard deviation.This method can solve the poor information and grey attributes in the periodic stability analysis of IMU,effectively enhance the robustness of the evaluation conclusion,and provide an effective data processing method for prolonging the life span of the instrument and equipment,and analyzing the environmental impact of storage.
作者
王顺宏
王刚
迟峰
田晓强
WANG Shun-hong;WANG Gang;CHI Feng;TIAN Xiao-qiang(The Rocket Force Universityof Engineering,Xi'an Shaxi 710025,China;The No.96743 Force,Tianshui Gansu 741000,China;No.96752 Force,Tonghua Jilin 134000,China;No.96902 Force,Beijing 122000,China)
出处
《计算机仿真》
北大核心
2019年第3期264-267,共4页
Computer Simulation
关键词
稳定性
模型
随机区间
Stability
Model
Random interval
