Yi Shenglun, Zorzi Mattia, Jin Xuebo, Su Tingli
Department of Information Engineering, University of Padova, Via Gradenigo 6/B, 35131 Padova, Italy.
School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
Sensors (Basel). 2024 Aug 14;24(16):5247. doi: 10.3390/s24165247.
In this paper, we propose a novel switched approach to perform smartphone-based pedestrian navigation tasks even in scenarios where GNSS signals are unavailable. Specifically, when GNSS signals are available, the proposed approach estimates both the position and the average bias affecting the measurements from the accelerometers. This average bias is then utilized to denoise the accelerometer data when GNSS signals are unavailable. We test the effectiveness of denoising the acceleration measurements through the estimated average bias by a synthetic example. The effectiveness of the proposed approach is then validated through a real experiment which is conducted along a pre-planned 150 m path.
在本文中，我们提出了一种新颖的切换方法，即使在全球导航卫星系统（GNSS）信号不可用的场景下，也能执行基于智能手机的行人导航任务。具体而言，当GNSS信号可用时，所提出的方法会估计位置以及影响加速度计测量值的平均偏差。然后，当GNSS信号不可用时，利用该平均偏差对加速度计数据进行去噪。我们通过一个综合示例测试了利用估计出的平均偏差对加速度测量值进行去噪的有效性。随后，通过沿着预先规划的150米路径进行的实际实验，验证了所提方法的有效性。
