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Improved least squares approaches for differential received signal strength-based localization with unknown transmit power

Danaee, M. R ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1007/s11277-019-06791-3
  3. Publisher: Springer , 2020
  4. Abstract:
  5. In this paper we consider the problem of improving unknown node localization by using differential received signal strength (DRSS). Many existing localization approaches, especially those using the least squares methods, either ignore nonlinear constraint among model parameters or utilize them inefficiently. In this paper, we develop four DRSS-based localization methods by utilizing different combinations of covariance and weight matrices. Each method constructs a two-stage procedure. During the first stage, an initial coarse position estimate is obtained. The second stage results the refined localization by accounting for nonlinear dependency among estimator variables. The proper choice among these proposed methods may be offered, depending on a particular signal to noise range. We implement these methods and compare them with some of the state-of-art methods in this particular problem domain and verify their performances by simulations. © 2019, Springer Science+Business Media, LLC, part of Springer Nature
  6. Keywords:
  7. Covariance matrix ; Differential received signal strength-based localization ; Improved least squares ; Uncooperative ; Unknown transmit power ; Covariance matrix ; Signal to noise ratio ; Least Square ; Least squares methods ; Least-squares approach ; Non-linear constraints ; Nonlinear dependencies ; Received signal strength ; Transmit power ; Uncooperative ; Least squares approximations
  8. Source: Wireless Personal Communications ; Volume 110, Issue 3 , 2020 , Pages 1373-1401
  9. URL: https://link.springer.com/article/10.1007/s11277-019-06791-3