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ACMI: FM-Based Indoor Localization via Autonomous Fingerprinting

delete2016-06-01
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K
Kyunghan Lee
I
Injong Rhee
DOI:10.1109/TMC.2015.2465372delete
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Abstract

Abstract

En 中文
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.
Keywords:
Indoor localization
FM signal
signal fingerprint
pattern matching
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Journal

IEEE Transactions on Mobile Computing cover
IEEE Transactions on Mobile Computing
IF:
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Microsoft
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North Carolina State University
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