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DC Field | Value | Language |
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dc.contributor.author | Mahapatra, R.K. | |
dc.contributor.author | Shet, N.S.V. | |
dc.date.accessioned | 2020-03-31T08:35:54Z | - |
dc.date.available | 2020-03-31T08:35:54Z | - |
dc.date.issued | 2018 | |
dc.identifier.citation | Arabian Journal for Science and Engineering, 2018, Vol.43, 8, pp.4145-4159 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/11928 | - |
dc.description.abstract | The primary focus in this paper is on position estimation of an unknown sensor node in indoor environment. Received signal strength (RSS)-based algorithm was used for position estimation in which Gaussian filter and averaging filter were used for distance estimation, and for localization, trilateration and least square estimation were used. IRIS motes from MEMSIC were used for the experiments and were configured in real time to record the RSSI. Effect on distance estimation and localization was studied in indoor environment by conducting several experiments. Simulation results show that the proposed sensor selection, distance estimation based on RSSI as well as localization method helps in improving accuracy of position estimation in different environmental conditions. 2017, King Fahd University of Petroleum & Minerals. | en_US |
dc.title | Localization Based on RSSI Exploiting Gaussian and Averaging Filter in Wireless Sensor Network | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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