文章摘要
张涛,徐晓苏.基于LS-SVM的捷联大失准角初始对准技术[J].高技术通讯(中文),2012,22(1):88~93
基于LS-SVM的捷联大失准角初始对准技术
An initial alignment technique for strapdown inertial navigation systems based on large misalignment angles
  修订日期:2010-08-24
DOI:
中文关键词: 捷联惯性导航系统(CINS), 初始对准, 大失准角模型, 最小二乘支持向量机(LS-SVM), 简化无迹卡尔曼滤波(SUKF)
英文关键词: strapdown inertial navigation system(SINS), initial alignment, large misalignment angle model, least squares support vector machine (LS-SVM), simplified unscented Kalman filter (SUKF)
基金项目:国家自然科学基金(60904088,60874092)资助项目
作者单位
张涛 东南大学仪器科学与工程学院;东南大学微惯性仪表与先进导航技术教育部重点实验室 
徐晓苏 东南大学仪器科学与工程学院;东南大学微惯性仪表与先进导航技术教育部重点实验室 
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中文摘要:
      针对捷联惯性导航系统(SINS)大失准角初始对准情况下非线性模型线性化导致模型不准确和影响对准精度的问题,设计了一种基于最小二乘支持向量机(LS SVM)的大失准角对准算法。该方法采用基于加性四元数误差(AQE)的大失准角误差方程,采用简化的无迹卡尔曼滤波器(UKF)来模拟LS SVM训练样本。捷联惯性导航系统和全球定位系统(GPS)的速度和位置误差作为LS SVM的输入样本,简化UKF得到的失准角经小波去噪后作为输出样本。LS SVM算法采用交叉验证法选择最佳的核函数参数。仿真结果表明,在大失准角下LS
英文摘要:
      To solve the problem that the linearization of the nonlinear model causes the model inaccurateness and the influences on alignment accuracy during the initial alignment of a strapdown inertial navigation system (SINS) in the circumstances of the large misalignment angle, the paper proposes an algorithm for large misalignment angle alignment based on least squares support vector machines(LS SVM). The method introduces large misalignment angle error equations based on additive quaternion error(AQE), and uses the simplified unscented Kalman filter(SUKF) to simulate training samples. The velocity and position errors between SINS and GPS are set as input samples of the LS SVM and misalignment angles which are the outputs of the SUKF are set as output samples after de noised by wavelet. Cross validation is used to choose the best kernel function parameters. The simulation results demonstrate that the LS SVM algorithm has the better performance on alignment time and accuracy than the SUKF and EKF.
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