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Indoor Floor Localization Based on Multi-Intelligent Sensors
ISPRS International Journal of Geo-Information ( IF 3.4 ) Pub Date : 2020-12-25 , DOI: 10.3390/ijgi10010006 Min Zhao , Danyang Qin , Ruolin Guo , Xinxin Wang
ISPRS International Journal of Geo-Information ( IF 3.4 ) Pub Date : 2020-12-25 , DOI: 10.3390/ijgi10010006 Min Zhao , Danyang Qin , Ruolin Guo , Xinxin Wang
With the continuous expansion of the market of indoor localization, the requirements of indoor localization technology are becoming higher and higher. Existing indoor floor localization (IFL) systems based on Wi-Fi signal and barometer data are susceptible to external environment changes, resulting in large errors. A method for indoor floor localization using multiple intelligent sensors (MIS-IFL) is proposed to decrease the localization errors, which consists of a fingerprint database construction phase and a floor localization phase. In the fingerprint database construction phase, data acquisition is performed using magnetometer sensor, accelerator sensor and gyro sensor in the smartphone. In the floor localization phase, an active pattern recognition is performed through the collaborative work of multiple intelligent sensors and machine learning classifiers. Then floor localization is performed using magnetic data mapping, Euclidean closest approximation and majority principle. Finally, the inter-floor detection link based on machine learning is added to improve the overall localization accuracy of MIS-IFL. The experimental results show that the performance of the proposed method is superior to the existing IFL.
中文翻译:
基于多智能传感器的室内地板定位
随着室内定位市场的不断扩大,室内定位技术的要求越来越高。现有的基于Wi-Fi信号和气压计数据的室内地板定位(IFL)系统容易受到外部环境变化的影响,从而导致较大的误差。提出了一种利用多个智能传感器(MIS-IFL)进行室内地板定位的方法,以减少定位误差,该方法由指纹数据库的构建阶段和地板定位阶段组成。在指纹数据库构建阶段,使用智能手机中的磁力计传感器,加速器传感器和陀螺仪传感器执行数据采集。在楼层本地化阶段,通过多个智能传感器和机器学习分类器的协同工作,可以进行主动模式识别。然后使用磁数据映射,欧几里得最近似和多数原理执行地板定位。最后,增加了基于机器学习的楼层间检测链接,以提高MIS-IFL的整体定位精度。实验结果表明,该方法的性能优于现有的IFL。
更新日期:2020-12-25
中文翻译:
基于多智能传感器的室内地板定位
随着室内定位市场的不断扩大,室内定位技术的要求越来越高。现有的基于Wi-Fi信号和气压计数据的室内地板定位(IFL)系统容易受到外部环境变化的影响,从而导致较大的误差。提出了一种利用多个智能传感器(MIS-IFL)进行室内地板定位的方法,以减少定位误差,该方法由指纹数据库的构建阶段和地板定位阶段组成。在指纹数据库构建阶段,使用智能手机中的磁力计传感器,加速器传感器和陀螺仪传感器执行数据采集。在楼层本地化阶段,通过多个智能传感器和机器学习分类器的协同工作,可以进行主动模式识别。然后使用磁数据映射,欧几里得最近似和多数原理执行地板定位。最后,增加了基于机器学习的楼层间检测链接,以提高MIS-IFL的整体定位精度。实验结果表明,该方法的性能优于现有的IFL。