Abstract
In order to detect and track a moving target using an IR-UWB radar in indoor environment, the signal processing system using filters is normally used. Basically, filters cut the clutters off from the received signal based on the pre-defined characteristics of the target or clutters. Therefore, if the target and clutters are clearly distinguished, filters can be useful. However, the positioning range of the radar can be severely limited when the target signal is not distinguished because of the effect of signal attenuation caused by the path loss. This paper presents a radar signal processing method using codebook-based background training model. While the filter based signal processing system predicts the errors, proposed method measures and stores the informations of background components in the radar signal. In this way, the proposed system can distinguish the target and background more accurately. Experimental results in this paper shows that the proposed system is more robust to signal attenuation.
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Acknowledgment
Following are results of a study on the “Leaders in INdustry-university Cooperation +” Project, supported by the Ministry of Education and National Research Foundation (NRF) of Korea. Also, this research was supported by Basic Science Research Program through the NRF (No. 2014R1A1A2059952).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Gang, HS., Park, JB., Pyun, JY. (2018). Real-Time Indoor Positioning System Based on Background Training Model Using IR-UWB Radar. In: Li, B., Shu, L., Zeng, D. (eds) Communications and Networking. ChinaCom 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 236. Springer, Cham. https://doi.org/10.1007/978-3-319-78130-3_37
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DOI: https://doi.org/10.1007/978-3-319-78130-3_37
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