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Sen. Netw."],"published-print":{"date-parts":[[2013,5]]},"abstract":"<jats:p>\n            Wireless sensor networks are typically composed of low-cost sensors that are deeply integrated in physical environments. As a result, the sensing performance of a wireless sensor network is inevitably undermined by biases in imperfect sensor hardware and the noises in data measurements. Although a variety of calibration methods have been proposed to address these issues, they often adopt the\n            <jats:italic>device-level<\/jats:italic>\n            approach that becomes intractable for moderate-to large-scale networks. In this article, we propose a two-tier\n            <jats:italic>system-level<\/jats:italic>\n            calibration approach for a class of sensor networks that employ data fusion to improve the sensing performance. In the first tier of our calibration approach, each sensor learns its local sensing model from noisy measurements using an online algorithm and only transmits a few model parameters. In the second tier, sensors' local sensing models are then calibrated to a common system sensing model. Our approach fairly distributes computation overhead among sensors and significantly reduces the communication overhead of calibration compared with the device-level approach. Based on this approach, we develop an\n            <jats:italic>optimal<\/jats:italic>\n            model calibration scheme that maximizes the target detection probability of a sensor network under bounded false alarm rate. Our approach is evaluated by both experiments on a testbed of TelosB motes and extensive simulations based on synthetic datasets as well as data traces collected in a real vehicle detection experiment. The results demonstrate that our system-level calibration approach can significantly boost the detection performance of sensor networks in scenarios with low signal-to-noise ratios.\n          <\/jats:p>","DOI":"10.1145\/2480730.2480731","type":"journal-article","created":{"date-parts":[[2013,6,5]],"date-time":"2013-06-05T12:09:34Z","timestamp":1370434174000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":31,"title":["System-level calibration for data fusion in wireless sensor networks"],"prefix":"10.1145","volume":"9","author":[{"given":"Rui","family":"Tan","sequence":"first","affiliation":[{"name":"Michigan State University, East Lansing, MI"}]},{"given":"Guoliang","family":"Xing","sequence":"additional","affiliation":[{"name":"Michigan State University, East Lansing, MI"}]},{"given":"Zhaohui","family":"Yuan","sequence":"additional","affiliation":[{"name":"Huadong Jiao Tong University, China"}]},{"given":"Xue","family":"Liu","sequence":"additional","affiliation":[{"name":"McGill University, Montreal, Quebec, Canada"}]},{"given":"Jianguo","family":"Yao","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, China"}]}],"member":"320","published-online":{"date-parts":[[2013,6,4]]},"reference":[{"volume-title":"Modern Methods for Robust Regression","author":"Andersen R.","key":"e_1_2_1_1_1","unstructured":"Andersen , R. 2007. Modern Methods for Robust Regression . Sage Publications . Andersen, R. 2007. Modern Methods for Robust Regression. Sage Publications."},{"key":"e_1_2_1_2_1","unstructured":"Astrom K. and Wittenmark B. 1994. Adaptive Control. Addison-Wesley.   Astrom K. and Wittenmark B. 1994. Adaptive Control. Addison-Wesley."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1236360.1236372"},{"volume-title":"Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'03)","author":"Bychkovskiy V.","key":"e_1_2_1_4_1","unstructured":"Bychkovskiy , V. , Megerian , S. , Estrin , D. , and Potkonjak , M . 2003. A collaborative approach to in-place sensor calibration . In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'03) . 301--316. Bychkovskiy, V., Megerian, S., Estrin, D., and Potkonjak, M. 2003. A collaborative approach to in-place sensor calibration. In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'03). 301--316."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2004.1261838"},{"key":"e_1_2_1_6_1","unstructured":"Crossbow. 2013. Mica and mica2 wireless measurement system datasheets. http:\/\/gyro.xbow.com\/Products\/Product_pdf_files\/Datasheets\/Wireless\/6020-0041-01_A_MICA.pdf.  Crossbow. 2013. Mica and mica2 wireless measurement system datasheets. http:\/\/gyro.xbow.com\/Products\/Product_pdf_files\/Datasheets\/Wireless\/6020-0041-01_A_MICA.pdf."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2004.03.020"},{"volume-title":"Proceedings of the 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP'07)","author":"Fabeck G.","key":"e_1_2_1_8_1","unstructured":"Fabeck , G. and Mathar , R . 2007. In-situ calibration of sensor networks for distributed detection applications . In Proceedings of the 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP'07) . Fabeck, G. and Mathar, R. 2007. In-situ calibration of sensor networks for distributed detection applications. In Proceedings of the 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP'07)."},{"volume-title":"Proceedings of the 2nd IEEE International Conference on Sensors (Sensors'03)","author":"Feng J.","key":"e_1_2_1_9_1","unstructured":"Feng , J. , Megerian , S. , and Potkonjak , M . 2003. Model-based calibration for sensor networks . In Proceedings of the 2nd IEEE International Conference on Sensors (Sensors'03) . 737--742. Feng, J., Megerian, S., and Potkonjak, M. 2003. Model-based calibration for sensor networks. In Proceedings of the 2nd IEEE International Conference on Sensors (Sensors'03). 737--742."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1021\/ac60201a006"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1098918.1098941"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/T-VT.1980.23859"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/990064.990096"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1322263.1322291"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/984622.984656"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1155\/S1110865703212075"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/79.985674"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-69170-9_21"},{"key":"e_1_2_1_19_1","first-page":"491","article-title":"Self-calibration of sensor networks","volume":"4743","author":"Moses R.","year":"2002","unstructured":"Moses , R. and Patterson , R. 2002 . 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