Multiple Sources Localization with Sparse Recovery under Log-normal Shadow Fading
Abstract
Localization based on received signal strength (RSS) has drawn great interest in the wireless sensor network (WSN). In this paper, we investigate the RSS-based multi-sources localization problem with unknown transmitted power under shadow fading. The log-normal shadowing effect is approximated through Fenton-Wilkinson (F-W) method and maximum likelihood estimation is adopted to optimize the RSS-based multiple sources localization problem. Moreover, we exploit a sparse recovery and weighted average of candidates (SR-WAC) based method to set up an initiation, which can efficiently approach a superior local optimal solution. It is shown from the simulation results that the proposed method has a much higher localization accuracy and outperforms the other
- Publication:
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arXiv e-prints
- Pub Date:
- March 2021
- DOI:
- 10.48550/arXiv.2105.15097
- arXiv:
- arXiv:2105.15097
- Bibcode:
- 2021arXiv210515097C
- Keywords:
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- Computer Science - Networking and Internet Architecture;
- Electrical Engineering and Systems Science - Signal Processing