Yan Suqing, Wu Chunping, Deng Honggao, Luo Xiaonan, Ji Yuanfa, Xiao Jianming
Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, Guilin 541004, China.
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.
Sensors (Basel). 2022 Jul 23;22(15):5505. doi: 10.3390/s22155505.
Accurate indoor location information has considerable social and economic value in applications, such as pedestrian heatmapping and indoor navigation. Ultrasonic-based approaches have received significant attention mainly since they have advantages in terms of positioning with temporal correlation. However, it is a great challenge to gain accurate indoor localization due to complex indoor environments such as non-uniform indoor facilities. To address this problem, we propose a fusion localization method in the indoor environment that integrates the localization information of inertial sensors and acoustic signals. Meanwhile, the threshold scheme is used to eliminate outliers during the positioning process. In this paper, the estimated location is fused by the adaptive distance weight for the time difference of arrival (TDOA) estimation and improved pedestrian dead reckoning (PDR) estimation. Three experimental scenes have been developed. The experimental results demonstrate that the proposed method has higher localization accuracy in determining the pedestrian location than the state-of-the-art methods. It resolves the problem of outliers in indoor acoustic signal localization and cumulative errors in inertial sensors. The proposed method achieves better performance in the trade-off between localization accuracy and low cost.
准确的室内位置信息在诸如行人热图绘制和室内导航等应用中具有相当大的社会和经济价值。基于超声波的方法主要因其在基于时间相关性的定位方面具有优势而受到了广泛关注。然而,由于诸如室内设施不均匀等复杂的室内环境,要获得准确的室内定位是一项巨大的挑战。为了解决这个问题,我们提出了一种室内环境中的融合定位方法,该方法整合了惯性传感器和声学信号的定位信息。同时,采用阈值方案在定位过程中消除异常值。在本文中,通过对到达时间差(TDOA)估计的自适应距离权重和改进的行人航位推算(PDR)估计来融合估计位置。开发了三个实验场景。实验结果表明,所提出的方法在确定行人位置方面比现有方法具有更高的定位精度。它解决了室内声学信号定位中的异常值问题以及惯性传感器中的累积误差问题。所提出的方法在定位精度和低成本之间的权衡中取得了更好的性能。