Continuous Estimation of Motion State in GPS/INS Integration Based on NARX Neural Network
作者单位：School of AutomationBeijing Institute of Technology School of Computer and Information EngineeringBeijing Technology and Business University
会议名称：《第37届中国控制会议》
会议日期：2018年
学科分类：12[管理学] 081802[工学-地球探测与信息技术] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 081105[工学-导航、制导与控制] 0818[工学-地质资源与地质工程] 0804[工学-仪器科学与技术] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Natural Science Foundation of China(No.61573061)
关 键 词：State estimation NARX neural network GPS INS information fusion
摘 要：The accurate estimation of motion state has been the key node in the control of motion systems. The traditional GPS/INS（Global Position System/Inertial Navigation System） integration may be invalid in the outage of GPS signals. The continuous estimation framework and method were proposed to estimate the location in different environments. Firstly, a continuous framework was designed combining the traditional GPS/INS integration and the intelligent neural network. The methods were switched according to the condition of sensors to realize the continuous estimation. Secondly, NARX（Nonlinear Autoregressive with Exogenous Inputs） neural network was built to model the nonlinear mapping relation between INS and GPS. The time series data were analyzed in NARX neural network to excavate the data features in the time dimension. Lastly, the experiment was conducted to verify the method proposed. And the results showed that the solution is valid in the motion state estimation with INS when GPS is in the outage.