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一种用于整合来自搭载 GNSS/IMU 的安卓智能手机的陀螺仪和加速度计不同速率数据的改进卡尔曼滤波器。

A Modified Kalman Filter for Integrating the Different Rate Data of Gyros and Accelerometers Retrieved from Android Smartphones in the GNSS/IMU Coupled Navigation.

机构信息

School of Geography, Geomatics and Planning, Jiangsu Normal University, 101 Rd. Shanghai, Xuzhou 221116, China.

School of Environment Science and Spatial Informatics, China University of Mining and Technology, No 1, Daxue Road, Xuzhou 221116, China.

出版信息

Sensors (Basel). 2020 Sep 12;20(18):5208. doi: 10.3390/s20185208.

Abstract

Recent study indicates that by using the inertial measurement unit (IMU) sensors inside smartphones, we can obtain similar navigation solutions to the professional ones. However, the sampling rates of the gyros and accelerometers inside some types of smartphones are not set in the same frequencies, i.e., the gyros of "Huawei p40" are in 50 Hz while the accelerometer is 100 Hz. The conventional method is resampling the higher frequency to the lower frequency ones, which means the resampled accelerometer will lose half frequency observations. In this work, a modified Kalman filter was proposed to integrate all these different rate IMU data in the GNSS/IMU-smartphone coupled navigation. To validate the proposed method, a terrestrial test with two different types of android smartphones was done. With the proposed method, a slight improvement of the attitude solutions can be seen in the experiments under the GNSS open-sky condition, and the obvious improvement of the attitude solutions can be witnessed at the simulated GNSS denied situation. The improvements by 45% and 23% of the horizontal position accuracy can be obtained from the experiments under the GNSS outage of 50 s in a straight line and 30 s in a turning line, respectively.

摘要

最近的研究表明,我们可以利用智能手机内部的惯性测量单元(IMU)传感器获得类似于专业导航解决方案的导航结果。然而,某些类型的智能手机内部陀螺仪和加速度计的采样率并没有设置在相同的频率上,例如,“华为 P40”的陀螺仪是 50 Hz,而加速度计是 100 Hz。传统的方法是将较高频率的传感器重采样到较低频率的传感器上,这意味着重采样后的加速度计将丢失一半的频率观测值。在这项工作中,提出了一种改进的卡尔曼滤波器,以整合 GNSS/IMU-智能手机耦合导航中所有不同速率的 IMU 数据。为了验证所提出的方法,我们在两种不同类型的安卓智能手机上进行了地面测试。在 GNSS 开放天空条件下的实验中,所提出的方法可以略微改善姿态解的精度,在模拟的 GNSS 拒止情况下,姿态解的精度有明显的提高。在 50 秒直线和 30 秒转弯的 GNSS 中断实验中,水平位置精度分别提高了 45%和 23%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c65/7570956/52f5689a2d90/sensors-20-05208-g001.jpg

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