Paper Info
Title
Distance Estimation Based On Statistical Models Of Received Signal Strength
Abstract
In this letter, we propose a new distance estimation method based on statistical models of a Received Signal Strength (RSS) at the receiver. The conventional distance estimator estimates the distance between the transmitter and the receiver based on the statistical average of the RSS when the receiver obtains instantaneous RSS and an estimate of the hyperparameters which consists of the path loss exponent and so on. However, it is well-known that instantaneous RSS does not always correspond to the average RSS because the RSS varies in accordance with a statistical model. Although the statistical model has been introduced for the hyperparameters estimation and the localization system, the conventional distance estimator has not yet utilized it. We introduce the statistical model to the distance estimator whose expected value of the estimate corresponds to true distance. Our theoretical analysis establishes that the proposed distance estimator is preferable to the conventional one in order to improve accuracy in the expected value of the distance estimate. Moreover, we evaluate the Mean Square Error (MSE) between true distance and the estimate. We provide evidence that the MSE is always proportional to the square of the distance if the estimate of the hyperparameters is ideally obtained.
Year
DOI
Venue
2016
10.1587/transfun.E99.A.199
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
Field
DocType
distance estimation, received signal strength, statistical model, mean square error
Mean squared error,Statistical model,Signal strength,Statistics,Mathematics
Journal
Volume
Issue
ISSN
E99A
1
1745-1337
Citations 
PageRank 
References 
1
0.63
4
Authors
5
Name
Order
Citations
PageRank
Masahiro Fujii11914.62
Yuma Hirota210.63
Hiroyuki Hatano32613.56
Atsushi Ito4127.50
Yu Watanabe52613.51