全球导航卫星系统应用
全球导航卫星系统增强
计算机科学
卫星系统
阻塞(统计)
惯性导航系统
卡尔曼滤波器
空中航行
平滑的
实时计算
卫星导航
信号(编程语言)
导航系统
全球定位系统
人工智能
电信
计算机视觉
惯性参考系
量子力学
物理
程序设计语言
计算机网络
作者
Mengke Wang,Peidong Yu,Yunzhi Li
标识
DOI:10.1051/e3sconf/202020602013
摘要
Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) are the most widely used navigation systems at present. Aiming at the limitations of a single system application, this paper uses kalman filter to fuse the pose information provided by GNSS and INS, respectively. GNSS has the characteristics of being easily affected by the environment but with high absolute positioning accuracy. INS has the characteristics of high sampling frequency and autonomous navigation, but the error accumulates with time. Combining the advantages of the two systems to achieve the purpose of obtaining higher-precision pose information. In addition, aiming at the problem that GNSS/INS integration cannot provide continuous, stable and reliable navigation solutions under the GNSS signal blocking environment, a smoothing post-processing algorithm for GNSS/INS integration is studied. Through experimental verification, this algorithm can effectively improve the pose accuracy under GNSS signal blocking environment.
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