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Light Linear RSS-Based Sensor Localization with Unknown Transmit Power by Tikhonov-regularization | ||
| AUT Journal of Electrical Engineering | ||
| مقاله 8، دوره 53، شماره 1، شهریور 2021، صفحه 77-86 اصل مقاله (1.06 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/eej.2021.19103.5380 | ||
| نویسندگان | ||
| Hassan Nazari1؛ M. R. Danaee* 2 | ||
| 1Department of Electronic and Electrical Engineering, Malek Ashtar University of Technology, Tehran, Iran | ||
| 2EE Dept., Imam Hossein Comprehensive University (IHCU), Tehran, Iran | ||
| چکیده | ||
| In this paper, we introduce a new linear received signal strength-based estimator for unknown node localization which its accuracy at low Signal-to-noise ratio (SNR) is better than many linear estimators and can compete with estimators based on the convex optimization, but it is much lighter than convex optimization-based estimators. The main ingredients in our proposed linear position estimator are to reformulate the localization problem in terms of Tikhonov-regularization and introduce a biased noise variable. The way that we apply for this reformulation avoids any possible linear approximation in which target position variables are involved, thus saving fair amount of information. The proposed algorithm is also indifferent to the transmit power and thus, applicable to either known or unknown transmit power scenarios. Simulation results show the efficacy of the proposed algorithm in comparison to the other methods for both typical RSS-based measurement data model and the modified model for indoor application. | ||
| کلیدواژه‌ها | ||
| Received signal strength (RSS)؛ node localization؛ linear least squares؛ Tikhonov-regularization؛ wireless؛ sensor network (WSN) | ||
| مراجع | ||
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