The Modeling and Prediction of Strapdown Inertial Measurement Unit based on Support Vector Regression and Particle Swarm Optimization

被引：0

作者：

Li, Shuying ^{[1
]}

Xuan Diwu ^{[1
]}

Li, Yiran ^{[1
]}

机构：

[1] Xian Univ Posts & Telecommun, Sch Automat, Xian, Peoples R China

来源：

2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019) | 2019年

基金：

中国国家自然科学基金;

关键词：

support vector regression; particle swarm optimization; stability prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Strapdown inertial measurement unit (SIMU) installed in a vehicle determines the navigation accuracy of the vehicle. However, the stability of SIMU changes with the storage time passing by, which influences the navigation accuracy of the vehicle. Thus, it is very necessary to establish a predication model which can predict the stability of SIMU and evaluate the performance of SIMU. This paper proposes a method to predict the SIMU stability. This algorithm is based on support vector regression and particle swarm optimization. The results expressed that support vector regression and particle swarm optimization can forecast the changing trend of SIMU accurately, which can provide the theoretical basis for evaluating the SIMU's performance.

引用

页码：1314 / 1318

页数：5