.png){kind=icon}
Return
Unknown Transmit Power RSSD Based Source Localization With Sensor Position Uncertainty
.png){kind=icon}
PRE
AI
DOI：10.1109/TCOMM.2015.2410300.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Source localization is an important field of research with numerous applications in signal processing and wireless communications. In this paper, we present a received signal strength difference (RSSD) based method to localize a source with unknown transmit power in the presence of sensor position uncertainty. It is an efficient low complexity technique which does not require transmit power estimation as with other approaches. This eliminates the uncertainty due to signal propagation parameter variations. A constrained adaptive weighted least squares technique is presented to obtain a least squares initial estimate (LSIE) of the source location. Then, this estimate is improved using a computationally efficient modified Newton method (MNM) with adaptive weights. The bias of the proposed LSIE-MNM method and the Cramer-Rao lower bound (CRLB) of the RSSD based measurement model are derived to determine the effect of sensor position uncertainties on the source location estimate. Results are presented which show that the proposed method achieves the CRLB when the SNR is sufficiently high.
Keywords:
Source localization
received signal strength difference (RSSD)
sensor position uncertainty
least squares
Newton method
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.3
Papers:
1.2W
Citations:
3.6W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveShareSaveShareSaveShareSave
View more