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Holding-Manner-Free Heading Change Estimation for Smartphone-based Indoor Positioning

机译:基于智能手机的室内定位的持有的WIRLES-WINESS-MEARGENT估计

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Smartphones have been a great platform for location-based services (LBS) and heading estimation is a key technique. In this paper, we proposed a heading change estimation algorithm based on inertial sensors built-in smartphones for indoor positioning. Compared with previous common approaches, it gives the users a larger freedom, not requiring fixed even specific holding manners. The algorithm consists of three main parts, including holding manner transition detection, equivalent vertical angular update and heading change calculation. Holding manner transition detection aims to separate the gyroscope measurement contribution caused by transitions from that of the user's heading change. Equivalent vertical angular rate is defined to recognize the heading change interval. Due to the low-precision of inertial sensors, heading change is calculated by tracing the ideologies of complementary filter and inertial frame alignment. It can also be obtained from the equivalent vertical angular rate directly for low accuracy requirement situation. In the case of known initial heading, the proposed method is converted to a heading estimation method. Experiment results show that the proposed method can detect the holding manner transition accurately and provides relatively good heading change estimation.
机译:智能手机是基于位置的服务(LBS)的一个很好的平台,标题估计是一个关键技术。在本文中,我们提出了一种基于惯性传感器的标题变化估计算法,内置智能手机进行室内定位。与以前的常见方法相比,它使用户更大的自由,不需要固定的甚至特定的举行方式。该算法由三个主要部分组成,包括保持方式转换检测,等效垂直角度更新和转向变化计算。保持方式过渡检测旨在将由用户的出版物变化的转换造成的陀螺仪测量贡献分离。等效垂直角速率被定义为识别出标题变化间隔。由于惯性传感器的低精度,通过跟踪互补滤波器的意识形态和惯性帧对准来计算出头变化。它也可以从等效的垂直角速率获得直接用于低精度要求情况。在已知初始标题的情况下,所提出的方法被转换为标题估计方法。实验结果表明,该方法可以准确地检测保持方式转变并提供相对良好的标题变化估计。

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