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PDR/GNSS Fusion Algorithm Based on Joint Heading Estimation

机译:基于联合航向估计的PDR / GNSS融合算法

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The performance of Pedestrian Dead Reckoning (PDR) based on a smartphone is limited due to the low-cost MEMS IMU. Heading and stride length estimation tend to accumulate errors over time and those errors lead to the failure of PDR. Considering that Global Navigation Satellite System (GNSS) provides absolute location information in outdoor applications, and the characteristics of estimation errors of GNSS are quite different from those of PDR. In this paper, we analyse the characteristics of two different types of errors first, then we propose a fusion positioning framework that can fuse PDR and GNSS information in real time. The joint estimations of heading and stride length are also given. The experimental results show that the fusion algorithm is superior to PDR or GNSS in heading estimation, anti-multipath and noise performance.
机译:由于低成本的MEMS IMU,基于智能手机的行人航位推算(PDR)的性能受到限制。航向和步幅长度估计会随时间累积误差,这些误差会导致PDR失败。考虑到全球导航卫星系统(GNSS)在室外应用中提供了绝对的位置信息,并且GNSS的估计误差与PDR的估计误差有很大不同。在本文中,我们首先分析了两种不同类型的错误的特征,然后提出了一种融合定位框架,该框架可以实时融合PDR和GNSS信息。还给出了航向和步幅长度的联合估计。实验结果表明,该融合算法在航向估计,抗多径和噪声性能方面均优于PDR或GNSS。

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