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首页> 外文期刊>IEEE transactions on mobile computing >ACMI: FM-Based Indoor Localization via Autonomous Fingerprinting
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ACMI: FM-Based Indoor Localization via Autonomous Fingerprinting

机译:ACMI:通过自主指纹进行基于FM的室内本地化

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We present ACMI, an FM-based indoor localization system that does not require proactive site profiling. ACMI constructs the fingerprint database based on pure estimation of indoor received signal strength (RSS) distribution, where only the signals transmitted from commercial FM radio stations are used. Based on extensive field measurement study, we established our own signal propagation model that harnesses FM radio characteristics and open information of FM transmission towers in combination with the floor-plan of a building. Output of the model is an RSS fingerprint database. Using the fingerprint database as a knowledge base, ACMI refines a positioning result via the two-step process; parameter calibration and path matching, during its runtime. Without site profiling, our evaluation indicates that ACMI in seven campus locations and three downtown buildings using eight distinguished FM stations finds positions with only about 6 and 10 meters of errors on average, respectively.
机译:我们提出了ACMI,这是一种基于FM的室内定位系统,不需要主动进行站点分析。 ACMI基于室内接收信号强度(RSS)分布的纯估计来构建指纹数据库,其中仅使用从商用FM广播电台发射的信号。在广泛的现场测量研究的基础上,我们建立了自己的信号传播模型,该模型利用FM无线电特性和FM传输塔的开放信息并结合建筑物的平面图。该模型的输出是RSS指纹数据库。 ACMI使用指纹数据库作为知识库,通过两步过程来优化定位结果。在运行期间进行参数校准和路径匹配。如果不进行站点概要分析,我们的评估表明,使用八个著名的FM电台的七个校园位置和三个市区建筑物中的ACMI所发现的位置平均分别只有大约6米和10米的误差。

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