Vehicle Dynamic Model Based Navigation Algorithm Requirement Analysis for Improving High Precision Inertial Navigation System

Q3 Mathematics
Bo-Sung Ko, Yong-Hun Kim, Joo-Han Lee, So-Jin Park, Seung Hyo Park, Jin Woo Song
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引用次数: 0

Abstract

We propose an idea of using VDM (Vehicle Dynamic Model) as a constraint of INS (Inertial Navigation System) for improving the long term navigation performance. In order to suppress long term INS error, a constrained Kalman filter is applied. Before developing the high precision INS with various sensors and techniques, M&S (Modeling & Simulation) step is performed to define and validate the necessary requirements of the development, which here in this research, the requirement of VDM quality is analyzed. M&S is constructed using a 6-DOF submarine dynamic model and a guidance-navigation control model. It is assumed that the navigation sensor is consisted with an inertial measurement unit, EM-Log (Electromagnetic Log), and DM (Depth Module). Monte-Carlo simulation results confirm the effectiveness of the VDM employed by the constrained Kalman filter and requirements for VDM error are also analyzed.
基于车辆动态模型的导航算法改进高精度惯性导航系统需求分析
为了提高惯性导航系统的长期导航性能,提出了一种利用车辆动态模型(Vehicle Dynamic Model, VDM)约束惯性导航系统的思想。为了抑制惯导系统的长期误差,采用了约束卡尔曼滤波器。在开发采用各种传感器和技术的高精度惯导系统之前,首先进行建模与仿真(M&S)步骤,以定义和验证开发的必要要求,在本研究中,分析了对VDM质量的要求。采用六自由度潜艇动力学模型和制导导航控制模型构建了M&S系统。假设导航传感器由惯性测量单元、EM-Log(电磁日志)和DM(深度模块)组成。蒙特卡罗仿真结果证实了约束卡尔曼滤波器所采用的VDM的有效性,并分析了对VDM误差的要求。
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CiteScore
1.50
自引率
0.00%
发文量
128
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