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• W2886219924 abstract "Multi-target localization methods for locating of the movingtarget in interested area monitored by Wireless Sensor Networks (WSNs) are nowadays a popular subject of study. The methods can be classified into two categories: range-free algorithm and range-based algorithm. In this work, we propose a novel multi-target localization method, which belongs to the category of range-based algorithm, by using a genetic algorithm (GA) for searching optimal solution of the objective function of multi-target localization. The objective function is only a group of linear equations with independent variables of acoustic energies calculated at each sensor-node in a WSN. However, application of the method, the accuracy of multi-target localization is sensitive to the SNR of the measured sound signals at each node, thus a denoising strategy should be inserted into the method. It turned out that the measured sound noise, comparing intrinsic sensor noise and environmental noise, may be considered as an Autoregressive Moving Average (ARMA) process. Thus, by building the ARMA model, the noise sequence commingled with the target signals can be predicted. As a consequence, the power of the noises can be subtracted from the measured sound signals for revealing the target signal's power. The results in present work demonstrate the advantage of the proposed method." @default.
• W2886219924 created "2018-08-22" @default.
• W2886219924 creator A5021065636 @default.
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• W2886219924 date "2018-01-01" @default.
• W2886219924 modified "2023-09-26" @default.
• W2886219924 title "Multi-targets localization based on ARMA and GA in WSNs" @default.
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• W2886219924 doi "https://doi.org/10.1051/matecconf/201818904015" @default.
• W2886219924 hasPublicationYear "2018" @default.
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