Pattern Matching Performance Analysis Based on Linear Models with Information Backscattered from RFID Tags

Pattern Matching Performance Analysis Based on Linear Models with Information Backscattered from... Pattern matching localization algorithms are commonly proposed in complex indoor environments. Received signal strength indicator (RSSI) of radio signals backscattered from passive ultra high frequency radio frequency identification (RFID) tags is commonly used as the pattern in matching process. Considering RSSI is severely affected by multipath propagation and noise, etc., more types of patterns will be a better choice for further study. In recent years, phase information is becoming more and more important for RFID-based systems. As for the period ambiguity problem of wrapped phase information, phase difference of arrival (PDOA) of double-frequency signals can be utilized as a type of pattern instead of phase of arrival corresponding to the propagation distance. In this paper, we combine RSSI and PDOA as a brand new type of pattern named RP. In previous study, only localization accuracy is considered to prove effective. It is hard to show the matching performance of the type of pattern with the following process of localization algorithms. Here we take advantage of the linear relationship between pattern Euclidean distance and geographic locations Euclidean distance of tags fixed in reference points to evaluate the distinctiveness performance of RP in matching. The linear correlation of the model is tested at each reference point with experimental data captured from indoor scenario. By evaluating these models statistically, we think RP is better than RSSI and PDOA as a pattern. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Wireless Information Networks Springer Journals

Pattern Matching Performance Analysis Based on Linear Models with Information Backscattered from RFID Tags

Loading next page...
 
/lp/springer_journal/pattern-matching-performance-analysis-based-on-linear-models-with-Z7uSALawV4
Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Electrical Engineering
ISSN
1068-9605
eISSN
1572-8129
D.O.I.
10.1007/s10776-017-0372-1
Publisher site
See Article on Publisher Site

Abstract

Pattern matching localization algorithms are commonly proposed in complex indoor environments. Received signal strength indicator (RSSI) of radio signals backscattered from passive ultra high frequency radio frequency identification (RFID) tags is commonly used as the pattern in matching process. Considering RSSI is severely affected by multipath propagation and noise, etc., more types of patterns will be a better choice for further study. In recent years, phase information is becoming more and more important for RFID-based systems. As for the period ambiguity problem of wrapped phase information, phase difference of arrival (PDOA) of double-frequency signals can be utilized as a type of pattern instead of phase of arrival corresponding to the propagation distance. In this paper, we combine RSSI and PDOA as a brand new type of pattern named RP. In previous study, only localization accuracy is considered to prove effective. It is hard to show the matching performance of the type of pattern with the following process of localization algorithms. Here we take advantage of the linear relationship between pattern Euclidean distance and geographic locations Euclidean distance of tags fixed in reference points to evaluate the distinctiveness performance of RP in matching. The linear correlation of the model is tested at each reference point with experimental data captured from indoor scenario. By evaluating these models statistically, we think RP is better than RSSI and PDOA as a pattern.

Journal

International Journal of Wireless Information NetworksSpringer Journals

Published: Sep 27, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off