Paper Info
Title
A Computationally Efficient Received Signal Strength Based Localization Algorithm in Closed-Form for Wireless Sensor Network.
Abstract
Ranging error is known to degrade significantly the target node localization accuracy. This paper investigates the use of computationally efficient positioning solution of least square (LS) in closed-form, to reduce localization accuracy loss caused by ranging error. For range-based node localization, the LS solution based on least square criterion has been confirmed to exhibit capability of optimum estimation but extensively achieve at a very complex calculation. In this paper we consider the problem how to acquire such LS solution provided with estimation performance at low complex calculation. In this paper, we use the Gauss noise model and use the weighted least squares criterion and the effective calculation method to solve the linearized equation derived from the RSS measurement, and put forward a new approach to estimate the performance of the target node location estimation. Based on the Fisher information matrix, the Cramér–Rao lower bound of target position estimation is derived based on received signal strength. We obviously indicate that the proposed algorithm can approximately achieve the LS solution in estimation performance at a markedly low complex calculation. Simulations are performed to show the improvement of the proposed algorithm.
Year
DOI
Venue
2017
https://doi.org/10.1007/s11063-017-9625-3
Neural Processing Letters
Keywords
Field
DocType
Target node localization,Received signal strength (RSS),Wireless sensor network (WSN),Cramér–Rao lower bound (CRLB)
Least squares,Gauss,Upper and lower bounds,Algorithm,Ranging,Fisher information,Complex calculation,Wireless sensor network,RSS,Mathematics
Journal
Volume
Issue
ISSN
46
3
1370-4621
Citations 
PageRank 
References 
1
0.35
15
Authors
3
Name
Order
Citations
PageRank
Xinrong Zhang110.35
Weili Xiong2285.92
Baoguo Xu37813.67