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GPS/INS/Odometer Data Fusion for Land Vehicle Localization in GPS Denied Environment

机译：GPS / INS /里程表数据融合用于GPS拒绝环境中的陆地车辆定位

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The main purpose of this paper is to present a fusion approach to bridge the period of Global Positioning System (GPS) outages using two proprioceptive sensors that are the Inertial Navigation System (INS) and the odometer in order to assure a continuous localization for land vehicle in urban areas where GPS signal blockage is very often. Odometer and GPS measures are exploited to correct inertial sensor errors. In fact, during GPS availability, INS is integrated with GPS to provide accurate localization solution; whereas during GPS outages, the odometer measurements are used to correct the INS error thereby improving the positioning accuracy and assuring the continuity of navigation solution. The problem of estimation of vehicle localization is realized by Kalman Filter (KF) that merges sensor measurements. The paper thus introduces results from simulation and real data.
机译：本文的主要目的是提出一种融合方法，使用两个本体感测传感器（惯性导航系统（INS）和里程表）来弥合全球定位系统（GPS）中断的时间段，以确保陆上车辆的连续定位在GPS信号阻塞非常频繁的城市地区。里程表和GPS措施用于纠正惯性传感器误差。实际上，在GPS可用期间，INS与GPS集成在一起以提供准确的定位解决方案。而在GPS中断期间，里程表的测量结果可用于校正INS误差，从而提高定位精度并确保导航解决方案的连续性。车辆定位估计的问题是通过合并传感器测量值的卡尔曼滤波器（KF）实现的。因此，本文介绍了来自仿真和实际数据的结果。

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