Erten, CesimKarataş, Ömer2019-07-302019-07-302009-09-14Erten, C. & Karataş, O. (2009). A robust localization framework to handle noisy measurements in wireless sensor networks. Paper presented at the 2009 24th International Symposium on Computer and Information Sciences, 709-714. doi:10.1109/ISCIS.2009.529191097814244502139781424450237https://hdl.handle.net/11729/1666http://dx.doi.org/10.1109/ISCIS.2009.5291910Partially supported by TUBITAK grant 106E071.We construct a robust localization framework to handle noisy measurements in wireless sensor networks. Traditionally many approaches employ the distance information gathered from ranging devices of the sensor nodes to achieve localization. However the measurements of these devices may contain noise both as hardware noise and as environmental noise due to the employment conditions of the network. It Is necessary to provide a general framework that handles such a noise in data and yet still be applicable within several localization algorithms. In order to handle noise in distance measurements, our framework utilizes convex constraints and confidence intervals of a random variable. At the end of the localization process nodes are assigned to a set of feasible regions with corresponding probabilities. The accuracy of the localization can be adjusted and the framework can easily be embedded to work within previously suggested localization algorithms.eninfo:eu-repo/semantics/closedAccessAlgorithmConfidence intervalConvex constraintsDistance informationEmployment conditionsEnvironmental noiseFeasible regionsLocalization algorithmNoisy measurementsProcess nodesInformation scienceRandom processesRandom variablesSensor networksSensor nodesTelecommunication equipmentWireless telecommunication systemsWireless sensor networksWorking environment noiseAcoustic noiseGlobal positioning systemHardwareDistance measurementNoise robustnessWeather forecastingOptical noiseRobust localization frameworkA robust localization framework to handle noisy measurements in wireless sensor networksConference Object709714N/AWOS:0002750242001252-s2.0-7394909096010.1109/ISCIS.2009.5291910N/A