Abstract
We address the problem of locating multiple nodes in a wireless sensor network with the use of received signal strength (RSS) measurements. In RSS based positioning, transmit power and path-loss factor are two environment dependent parameters which may be uncertain or unknown. For unknown transmit powers, we devise two-step weighted least squares (WLS) and maximum likelihood (ML) algorithms for node localization. The mean square error of the former is analyzed in the presence of zero-mean white Gaussian disturbances. When both transmit powers and path-loss factors are unavailable, two nonlinear least squares estimators, namely, the direct ML approach and combination of linear least squares and ML algorithm, are developed. Numerical examples are also included to evaluate the localization accuracy of the proposed estimators by comparing with two existing node positioning methods and the Cramér-Rao lower bound. © 2013 Elsevier Inc.
| Original language | English |
|---|---|
| Pages (from-to) | 41-50 |
| Journal | Digital Signal Processing: A Review Journal |
| Volume | 25 |
| Issue number | 1 |
| Online published | 4 Nov 2013 |
| DOIs | |
| Publication status | Published - Feb 2014 |
Research Keywords
- Positioning algorithm
- Received signal strength
- Source localization
- Wireless sensor network
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