Wireless Sensor Networks (WSNs) are network of low size and less complex devices denoted as sensor nodes that can sense the environment and communicate the recorded parameters like temperature, sound, pollution levels, humidity, speed, pressure etc. Localization is one of the fundamental requirements of WSNs. The estimation of localization error for either a stationary or mobile sensor node can be done with the help of beacons and in a two dimensional network an unknown sensor node can estimate its location if there are three or more beacon nodes in its range. If the percentage of beacons is high, it is easier to perform localization, but, the cost and energy consumption of the network also increases. To estimate the localization error of the mobile node the Gauss Newton method is implemented in this paper. The implemented method is based on a procedure in which repetition of a sequence of operations yields results successively closer to a desired result for estimation of localization error. The proposed method is based on an iterative process and thus depends on the number of rounds. For simulations, the beacon nodes are placed on the vertices of a two dimensional square field along with a random mobile node placed inside the field. The implemented method estimates localization error only for a single mobile node with respect to four beacon nodes and computes its position through multilateration by means of information transmitted from the beacon nodes. The simulations are performed on a two dimensional square field using MATLAB 7.1 and the results of the proposed method are compared with existing method to see the effectiveness.
{"title":"Localization Error Estimation Technique for a Randomly Deployed Mobile Sensor Node","authors":"Sunita Kumawat, D. Verma","doi":"10.2139/ssrn.3558344","DOIUrl":"https://doi.org/10.2139/ssrn.3558344","url":null,"abstract":"Wireless Sensor Networks (WSNs) are network of low size and less complex devices denoted as sensor nodes that can sense the environment and communicate the recorded parameters like temperature, sound, pollution levels, humidity, speed, pressure etc. Localization is one of the fundamental requirements of WSNs. The estimation of localization error for either a stationary or mobile sensor node can be done with the help of beacons and in a two dimensional network an unknown sensor node can estimate its location if there are three or more beacon nodes in its range. If the percentage of beacons is high, it is easier to perform localization, but, the cost and energy consumption of the network also increases. To estimate the localization error of the mobile node the Gauss Newton method is implemented in this paper. The implemented method is based on a procedure in which repetition of a sequence of operations yields results successively closer to a desired result for estimation of localization error. The proposed method is based on an iterative process and thus depends on the number of rounds. For simulations, the beacon nodes are placed on the vertices of a two dimensional square field along with a random mobile node placed inside the field. The implemented method estimates localization error only for a single mobile node with respect to four beacon nodes and computes its position through multilateration by means of information transmitted from the beacon nodes. The simulations are performed on a two dimensional square field using MATLAB 7.1 and the results of the proposed method are compared with existing method to see the effectiveness.","PeriodicalId":201102,"journal":{"name":"4th International Conference: Innovative Advancement in Engineering & Technology (IAET) 2020","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132469228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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