Elevation accuracy improvement in mobile devices by implementing artificial neural networks

IF 1.2 Q4 TELECOMMUNICATIONS Journal of Location Based Services Pub Date : 2022-12-22 DOI:10.1080/17489725.2022.2157898
Elias Issawy, B. Levy, S. Dalyot
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引用次数: 0

Abstract

ABSTRACT An important feature of mobile devices relates to positioning, mainly relying on the global navigation satellite system sensor. In optimal conditions, this sensor provides horizontal positioning sufficient for most location-based services. The elevation, on the other hand, still lacks sufficient accuracy and reliability – mostly due to mobile device inadequacies that stem from technological limitations and environmental and physical conditions, which impact the observations quality. We suggest augmenting the elevation measurements of this sensor with measurements from supplementary embedded mobile device sensors, such as barometers and accelerometers, and with data from external mapping and environmental databases, namely topography and weather. We developed an artificial neural network deep-learning model that identifies parameter values for producing the highest predictive accuracy of the elevation value while relying on a comprehensive set of measurements. Our findings indicate very promising results, whereby we enhanced the elevation accuracy of testing data by 428%, while significantly reducing the elevation variance. These results show that using supplementary measurements and data improves elevation values while significantly reducing errors commonly associated with mobile device global navigation satellite system sensors. The proposed method has the capacity to improve outdoor kinematic positioning for location-based services, with a focus on urban and concealed areas.
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利用人工神经网络提高移动设备的高程精度
移动设备的一个重要特征与定位有关,主要依靠卫星全球导航系统的传感器。在最佳条件下,该传感器提供水平定位,足以满足大多数基于位置的服务。另一方面,高程仍然缺乏足够的准确性和可靠性,这主要是由于技术限制以及环境和物理条件导致的移动设备不足,从而影响了观测质量。我们建议通过附加的嵌入式移动设备传感器(如气压计和加速度计)以及外部地图和环境数据库(即地形和天气)的数据来增强该传感器的高程测量。我们开发了一个人工神经网络深度学习模型,该模型可以识别参数值,从而在依赖于一组全面的测量值的情况下产生最高的高程预测精度。我们的研究结果显示了非常有希望的结果,我们将测试数据的高程精度提高了428%,同时显著降低了高程方差。这些结果表明,使用补充测量和数据可以提高高程值,同时显著降低通常与移动设备全球导航卫星系统传感器相关的误差。所提出的方法能够改善基于位置服务的户外运动定位,重点是城市和隐蔽区域。
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来源期刊
CiteScore
3.70
自引率
8.70%
发文量
12
期刊介绍: The aim of this interdisciplinary and international journal is to provide a forum for the exchange of original ideas, techniques, designs and experiences in the rapidly growing field of location based services on networked mobile devices. It is intended to interest those who design, implement and deliver location based services in a wide range of contexts. Published research will span the field from location based computing and next-generation interfaces through telecom location architectures to business models and the social implications of this technology. The diversity of content echoes the extended nature of the chain of players required to make location based services a reality.
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