| 多传感器组合导航系统研究 |
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| 引用本文： | 迟凤阳,高伟.多传感器组合导航系统研究[J].海洋测绘,2017(5):34-38. |
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| 作者姓名： | 迟凤阳 高伟 |
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| 作者单位： | ;1.哈尔滨工业大学电气工程及自动化学院 |
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| 基金项目： | 国家自然科学基金(51379042) |
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| 摘 要： | 为了满足水下航行器高精度导航定位的需求,建立了多传感器组合导航的系统模型。针对信息融合过程中出现的非线性环节,在传统联邦滤波器的基础上,提出了基于粒子滤波的混合联邦滤波器。其中,线性子系统采用卡尔曼滤波算法进行滤波估计,非线性子系统采用粒子滤波算法进行滤波估计。计算机仿真分析表明,该混合联邦滤波算法能够将线性和非线性子系统的滤波结果很好地融合起来,提高了组合导航系统的定位精度。
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| 关 键 词： | 水下航行器 多传感器 组合导航 粒子滤波 混合联邦滤波 |
Multi-sensor Integrated Navigation System |
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| CHI Fengyang,GAO Wei.Multi-sensor Integrated Navigation System[J].Hydrographic Surveying and Charting,2017(5):34-38. |
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| Authors: | CHI Fengyang GAO Wei |
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| Institution: | School of Electrical Engineering and Automation,Harbin Institute of Technology,Harbin 150001 ,China |
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| Abstract: | In order to meet the needs of high-precision navigation and positioning for the Autonomous Underwater Vehicle (AUV),the multi-Sensor integrated navigation system model is established.The mixed federal filter is proposed based on the traditional federal filter to aim at the non-linear course in the information fusion process.The Kalman filter is applied in the linear subsystem and particle filter is applied in the non-linear subsystem.The computer simulation results show that the linear and nonlinear filtering subsystem can be well fused together by the mixed federal filtering algorithm,and the navigation positioning accuracy is greatly improved. |
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