Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment Based on Power Inversion and Complex-Valued Neural Networks

Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment... We propose two-stage null-steering direction-of-arrival (DoA) estimation of ultra wideband (UWB) signals with power inversion algorithm and complex spatio-temporal neural network (CVSTNN). This method can estimate DoA more accurately than conventional methods in narrowband interference (NBI) environment. For null steering in UWB systems, it is necessary to adjust the amplitude and phase of tapped delay lines (TDLs) of CVSTNN. However, with a conventional CVSTNN, it often fails to estimate the arrival direction because of the NBI. We aim to reduce the influence of NBI in the learning process to avoid falling into a local solution by setting the initial weights of the TDLs with power inversion. In simulation results, it is shown that the two-stage method can realize higher DoA estimation accuracy than conventional methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neural Processing Letters Springer Journals

Direction-of-Arrival Estimation of Ultra-Wideband Signals in Narrowband Interference Environment Based on Power Inversion and Complex-Valued Neural Networks

Loading next page...
 
/lp/springer_journal/direction-of-arrival-estimation-of-ultra-wideband-signals-in-2R0p2J0Foc
Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Complex Systems; Computational Intelligence
ISSN
1370-4621
eISSN
1573-773X
D.O.I.
10.1007/s11063-017-9669-4
Publisher site
See Article on Publisher Site

Abstract

We propose two-stage null-steering direction-of-arrival (DoA) estimation of ultra wideband (UWB) signals with power inversion algorithm and complex spatio-temporal neural network (CVSTNN). This method can estimate DoA more accurately than conventional methods in narrowband interference (NBI) environment. For null steering in UWB systems, it is necessary to adjust the amplitude and phase of tapped delay lines (TDLs) of CVSTNN. However, with a conventional CVSTNN, it often fails to estimate the arrival direction because of the NBI. We aim to reduce the influence of NBI in the learning process to avoid falling into a local solution by setting the initial weights of the TDLs with power inversion. In simulation results, it is shown that the two-stage method can realize higher DoA estimation accuracy than conventional methods.

Journal

Neural Processing LettersSpringer Journals

Published: Jul 20, 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