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- W1932803717 abstract "Considering the localization estimation issue in mixed line-of-sight (LOS)/non-LOS(NLOS) environments based on received signal strength (RSS) measurements in wireless sensor networks, a grid-based correlation method based on the relationship between distance and RSS is proposed in this paper. The Maximum-Likelihood (ML) estimator is appended to further improve the localization accuracy. Furthermore, in order to reduce computation load and enhance performance, an improved recursively version with NLOS mitigation is also proposed. The most advantages of the proposed localization algorithm is that, it does not need any prior knowledge of the propagation model parameters and therefore does not need any offline calibration effort to calibrate the model parameters in harsh environments, which makes it more convenient for rapid implementation in practical applications. The simulation and experimental results evidence that the proposed localization algorithm exhibits good localization performance and flexibilities for different devices." @default.
- W1932803717 created "2016-06-24" @default.
- W1932803717 date "2015-01-31" @default.
- W1932803717 modified "2023-09-30" @default.
- W1932803717 title "Grid-based Correlation Localization Method in Mixed Line-of-Sight/Non-Line-of-Sight Environments" @default.
- W1932803717 cites W1487150352 @default.
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- W1932803717 doi "https://doi.org/10.3837/tiis.2015.01.006" @default.
- W1932803717 hasPublicationYear "2015" @default.
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