Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65339
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Title: A statistical approach for site error correction in lightning location networks with DF/TOA technique and its application results
Authors: Lu, T
Chen, M 
Du, Y 
Qiu, Z
Issue Date: 1-Feb-2017
Source: Atmospheric research, 1 Feb. 2017, v. 184, p. 103-111
Abstract: Lightning location network (LLN) with DF/TOA (direction-finder/time-of-arrival) combined technique has been widely used in the world. However, the accuracy of the lightning data from such LLNs has still been restricted by “site error”, especially for those detected only by two DF/TOA sensors. In this paper we practice a statistical approach for evaluation and correction of “site error” for DF/TOA type LLN based on its lightning data. By comparing lightning locations recorded by at least 4 sensors between DF and TOA techniques, the spatial characteristics of “site error” for each sensor in the network can be obtained. The obtained “site error” then can be used to improve the accuracy of lightning locations especially those recorded by only 2 sensors. With this approach, the “site error” patterns for 23 sensors in Yunnan LLN are obtained. The features of these site error patterns are in good consistency with those in literature. Significant differences in lightning locations before and after “site error” corrections indicate that the proposed approach works effectively.
Keywords: Direction finder
Lightning location network
Site error
Time of arrival
Publisher: Elsevier
Journal: Atmospheric research 
EISSN: 0169-8095
DOI: 10.1016/j.atmosres.2016.10.009
Rights: © 2016 Elsevier B.V. All rights reserved.
© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Lu, T., Chen, M., Du, Y., & Qiu, Z. (2017). A statistical approach for site error correction in lightning location networks with DF/TOA technique and its application results. Atmospheric Research, 184, 103-111 is available at https://doi.org/10.1016/j.atmosres.2016.10.009.
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