android smartphones

  • 文章类型: Journal Article
    With the development of Global Navigation Satellite System (GNSS) and the opening of Application Programming Interface (API) of Android terminals, the positioning research of Android terminals has attracted the attention of GNSS community. In this paper, three static experiments were conducted to analyze the raw GNSS observations quality and positioning performances of the smartphones. For the two experimental smartphones, the numbers of visible satellites with dual-frequency signals are unstable and not enough for dual-frequency Precise Point Positioning (PPP) processing all through the day. Therefore, the ionosphere-constrained single-frequency PPP model was employed to improve the positioning with the smartphones, and its performance was evaluated and compared with those of the Single Point Positioning (SPP) and the traditional PPP models. The results show that horizontal positioning accuracies of the smartphones with the improved PPP model are better than 1 m, while those with the SPP and the traditional PPP models are about 2 m.
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  • 文章类型: Letter
    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.
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  • 文章类型: Journal Article
    实时运动(RTK)技术由于其高精度和实时定位而在现代社会中得到了广泛的应用。AndroidP的出现和BCM47755芯片组的应用使在智能手机上使用单频RTK和双频RTK成为可能。小米米8是第一款配备BCM47755芯片组的双频全球导航卫星系统(GNSS)智能手机。然而,由于卫星信号可能被建筑物和树木阻挡,因此RTK在城市地区的性能要比在开阔天空下的性能差得多。RTK无法提供某些特定区域的定位结果,例如城市峡谷和立交桥下的十字路口。本文将RTK与基于IMU的行人导航算法相结合。我们利用基于智能手机微机电系统(MEMS)惯性测量单元(IMU)的姿态和航向参考系统(AHRS)算法和零速度更新(ZUPT)算法来辅助RTK,以提高城市地区的定位性能。进行了一些测试以验证RTK在小米Mi8上的性能,我们分别评估了RTK在城市地区使用和不使用基于IMU的行人导航算法的情况下的性能。实际测试结果表明,在基于IMU的行人导航算法的辅助下,RTK比没有它的情况下更具鲁棒性和适应性。
    Real-time kinematic (RTK) technique is widely used in modern society because of its high accuracy and real-time positioning. The appearance of Android P and the application of BCM47755 chipset make it possible to use single-frequency RTK and dual-frequency RTK on smartphones. The Xiaomi Mi 8 is the first dual-frequency Global Navigation Satellite System (GNSS) smartphone equipped with BCM47755 chipset. However, the performance of RTK in urban areas is much poorer compared with its performance under the open sky because the satellite signals can be blocked by the buildings and trees. RTK can\'t provide the positioning results in some specific areas such as the urban canyons and the crossings under an overpass. This paper combines RTK with an IMU-based pedestrian navigation algorithm. We utilize attitude and heading reference system (AHRS) algorithm and zero velocity update (ZUPT) algorithm based on micro electro mechanical systems (MEMS) inertial measurement unit (IMU) in smartphones to assist RTK for the sake of improving positioning performance in urban areas. Some tests are carried out to verify the performance of RTK on the Xiaomi Mi 8 and we respectively assess the performances of RTK with and without the assistance of an IMU-based pedestrian navigation algorithm in urban areas. Results on actual tests show RTK with the assistance of an IMU-based pedestrian navigation algorithm is more robust and adaptable to complex environments than that without it.
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