基于扩展卡尔曼滤波器的INS/WSN无偏紧组合方法(英文)  

Unbiased tightly-coupled INS/WSN integrated navigation based on extended Kalman filter

作　　者：徐元[1,2] 陈熙源[1,2] 李庆华[3,1] 

机构地区：[1]东南大学仪器科学与工程学院,南京210096 [2]东南大学 微惯性仪表与先进导航技术教育部重点实验室,南京210096 [3]山东轻工业学院电气工程与自动化学院,济南250353

出　　处：《中国惯性技术学报》2012年第3期292-295,299,共5页Journal of Chinese Inertial Technology

基　　金：国家重点基础研究发展计划(973计划)(2009CB724002);国家自然科学基金资助项目(50975049);高等学校博士学科点专项科研基金资助课题(20110092110039);江苏省“六大人才高峰”资助项目(2008143);江苏省普通高校研究生科研创新计划(CXLX_0101)

摘　　要：为了减少传统组合导航方法中舍去泰勒展开式的高次项对导航精度的影响,提出了一种基于扩展卡尔曼滤波的INS/WSN无偏紧组合方法。这种方法采用INS在本地相对坐标系的位置和速度误差作为系统变量,观测方程中未知节点理想的位置和速度被INS测量得到的位置和速度与其预估误差的差值替代。仿真结果显示,本文提出的方法平均位置误差比松组合方法降低20%左右,平均速度误差比松组合方法降低80%左右。In order to reduce the influence on the precision of traditional integrated navigation when ignoring the higher-order terms in Taylor expansion,an unbiased tightly-coupled integration of Inertial Navigation System（INS） with Wireless Sensor Network（WSN） based on Extended Kalman Filter（EKF） is proposed.This method employs position error and velocity error of INS in the relative coordinates as the system state variables.In the measurement equation,the ideal position values at unknown nodes are replaced by the INS-measured positions and their error estimations,and the ideal velocity values at unknown nodes are replaced by the INS-measured velocities and their error estimations.Simulation results show that the proposed approach has effectively reduced the mean error of the position by about 20% compared with loosely-coupled integration,and the mean error of the velocity has been decreased by about 80% compared with loosely coupled mode.

关 键 词：惯性导航系统 无线传感器网络 紧组合 扩展卡尔曼滤波 

分 类 号：U666.1[交通运输工程—船舶及航道工程]