Accuracy and stability analysis of path loss exponent measurement for localization in wireless sensor network
In wireless sensor network localization, path loss model is often used to provide a conversion between distance and received signal strength (RSS). Path loss exponent is one of the main environmental parameters for path loss model to characterize the rate of conversion. Therefore, the accuracy of pa...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Advanced Institute of Convergence Information Technology
2013
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| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/202/1/Pu%20Chuan%20Chin%20-%20Accuracy%20and%20Stability%20analysis%20of%20path%20loss%20exponenet%20measurement%20for%20localization%20in%20wireless%20sensor%20network.pdf http://eprints.sunway.edu.my/202/ |
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| Summary: | In wireless sensor network localization, path loss model is often used to provide a conversion between distance and received signal strength (RSS). Path loss exponent is one of the main environmental parameters for path loss model to characterize the rate of conversion. Therefore, the accuracy of path loss exponent directly influences the results of RSS-to-distance conversion. When the conversion requires distance estimation from RSS value, small error of measured path loss exponent could lead to large error of the conversion output. To improve the localization results, the approaches of measuring accurate parameters from different environments have become important. Different approaches provide different measurement stabilities, depending on the performance and robustness of the approach. This paper presents four calibration approaches to provide measurements of path loss exponent based on measurement arrangement and transmitter/receiver node’s allocation. These include one-line measurement, online-update spread locations measurement, online-update small-to big rectangular measurement, and online-update big-to-small rectangular measurement. The first two are general approaches, and the last two are our newly proposed approaches. Based on our research experiments, a comparison is presented among the four approaches in terms of accuracy and stability. The results show that both online-update rectangular measurements have better stability of measurements. For accuracy of measurement, online-update big-to-small rectangular measurement provides the best result after convergence. |
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