![It is my privilege to present the print version of the [Volume 6 Issue 3] of our CurrentTrends in Signal
Processing, 2016. The intension of CTSP is to create an atmosphere that stimulates vision, research
andgrowthintheareaof Signalprocessing.
Timely publication, honest communication, comprehensive editing and trust with authors and
readers have been the hallmark of our journals. STM Journals provide a platform for scholarly
research articles to be published in journals of international standards. STM journals strive to publish
qualitypaperinrecordtime,makingitaleaderinserviceandbusiness offerings.
The aim and scope of STM Journals is to provide an academic medium and an important reference
for the advancement and dissemination of research results that support high level learning, teaching
andresearchinalltheScientific,TechnicalandMedicaldomains.
Finally, I express my sincere gratitude to our Editorial/ Reviewer board, Authors and publication
team for their continued support and invaluable contributions and suggestions in the form of
authoring writeups/reviewing and providing constructive comments for the advancement of the
journals.With regards to their due continuous support and co-operation, we have been able to publish
qualityResearch/Reviewsfindingsfor our customersbase.
Ihopeyouwillenjoyreadingthisissue andwewelcomeyourfeedbackonanyaspectof theJournal.
Dr.ArchanaMehrotra
ManagingDirector
STM Journals
Director's Desk
STM JOURNALS](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-8-320.jpg)
![CTSP (2016) 1-8 © STM Journals 2016. All Rights Reserved Page 1
Current Trends in Signal Processing
ISSN: 2277-6176(online), ISSN: 2321-4252(print)
Volume 6, Issue 3
www.stmjournals.com
Efficient Partial Update Algorithm over Wireless
Networks
Rupali Dewda*, Vijay Barfa
Department of Electronics and Communication, Rishiraj Institute of Technology, Indore,
Madhya Pradesh, India
Department of Electronics, Hathway Cable and Datacom Ltd., Indore, Madhya Pradesh, India
Abstract
Adaptive partial update algorithm is developed based on incremental method. The proposed
algorithm applies in real time changing environment. The proposed algorithm responds to
linear estimation with nodes in cooperative manner and less number of computations. The
algorithm has powerful advantage is that it requires less number of coefficient and reduced
computational and communication complexity in wireless sensor network. It is efficient
because it has power of solving distributed estimation and optimization by learning
mechanism. In wireless sensor networks there are various applications that involve
phenomenon in which space parameter are varying like surveillance, environment monitoring,
battle field, precision agriculture and medical application. In this paper three algorithms;
sequential partial update, stochastic partial update and max partial update are compared in
terms of mean square error (MSE). Performance characteristic and complexity analysis of
each algorithm are compared with MATLAB simulation.
Keywords: Incremental network, Sequential partial update, stochastic partial update, Max
partial update, MSE
INTRODUCTION
A wireless sensor networks (WSNs) composed
of an array of sensor nodes, i.e., tiny
embedded devices, which are distributed in the
geographical area, which collect information
or investigate special events and communicate
in a wireless manner [1]. The adaptive
distributed strategy, which relies on the
incremental mode, is the process of
cooperation between distinct nodes; these
nodes perform local computation and share the
result with the neighbouring nodes. The
resulting algorithm is cooperative, distributed,
and able to respond in real time change in
environment [2]. The nodes, which we also
interchangeably call agents, consist of at least
three main components: process units, sensing
devices and a wireless transmit-receive unit. In
more advance sensor networks, nodes are also
equipped with actuators to take action
according to the command issued from a
control unit.
Due to their vast applications, efficient design
and implementation of wireless sensor
networks have become an area of current
research [2]. Since the nodes in a network
function with small and limited battery power
and usually nonrenewable resources, it is
important to design the networks with less
communication among the nodes to estimate
the required parameter vector because
communication and computation consumes
most of the energy [2, 3]. Adaptive distributed
strategies with incremental mode of
communication focused on reduction in
communication complexity among the nodes
by restricting a particular node receiving and
transmitting to the predefined immediate
nodes only instead of every node of the
network [4, 5].
In this paper, we study and develop distributed
adaptive strategies for monitoring time-
varying physical phenomenon in sensor
network under real-world limitation and
change in environment condition.
In this paper, incremental partial update
strategies are proposed for weight update,](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-10-320.jpg)
![CTSP (2016) 9-15 © STM Journals 2016. All Rights Reserved Page 1
Current Trends in Signal Processing
ISSN: 2277-6176(online), ISSN: 2321-4252(print)
Volume 6, Issue 3
www.stmjournals.com
Elimination of Noise on ECG Signal Using Adaptive Filter
ShabnamTahmin*, Zeenat Afroze
Department of Electrical and Electronics Engineering, American International University-Bangladesh,
Bangladesh
Abstract
There are various biomedical signals present in the human body, by examining these
biomedical signal one can check the health condition of a person who is clinically fit or not.
Electrocardiogram (ECG) is one of them. ECG plays an important role in the primary
diagnosis, prognosis and survival analysis of heart diseases. This ECG signal is corrupted by
various noises like power line interference, baseline wandering etc. One way to remove this
noise is filtering the signal. This paper will present the performance of adaptive filter on ECG
signal. Diseases can be found by mixing power line interference with the ECG signal. We
have used the advanced adaptive filtering technique with Least Mean Square Algorithm for
the removal of power line interference from the ECG signal. Also, we have changed different
parameter of adaptive filter and we analyzed the performance of algorithm in terms of Signal
to Noise Ratio (SNR) improvement.
Keywords: ECG Signal, adaptive filter, least mean square (LMS), signal to noise ratio (SNR)
INTRODUCTION
The electrocardiograph (ECG) is an
instrument, which records the electrical
activity of the heart. A cleaned ECG signal
provides necessary information about the
electrophysiology of the heart diseases and
ischemic changes that may occur. It provides
valuable information about the functional
aspects of the heart and cardiovascular system.
The ECG works mostly by detecting and
amplifying the tiny electrical changes on the
skin that are caused when the heart muscle
"depolarizes" during each heartbeat. This is
detected as tiny rises and falls in the voltage
between two electrodes placed either side of
the heart, which is displayed as a wavy line
either on a screen or on a paper [1]. This
display indicates the overall rhythm of the
heart and weaknesses in different parts of the
heart muscle, so it is very important to get the
ECG signal clean and free from noise [1].
ECG signal generated from human body are
often very weak so as to be easily covered by
background noise. The noise in the ECG
signals occur due to various reasons like
electromagnetic interference due to ubiquitous
supply lines and plugs, movement of patient,
signals generated by other organs and
impedance mismatching between electrodes
[2]. Hence, the ECG signals can be corrupted
by various types of noises such as Power line
interference, Electrode contact noise, Motion
artifact, Muscle contraction, Base line drift,
Instrumental noise generated by electronic
devices [2]. ECG signal has frequency range
from 0.5 to 80 Hz and power line interference
introduces 50 to 60 Hz frequency component
in that signal which is the major cause of
corruption of ECG. Various methods have
been employed for the removal of power line
interference from ECG signals. One of them is
using an adaptive filter.
SIGNIFICANT FEATURES OF ECG
WAVEFORM
ECG records carrier information about
abnormalities or responses to certain
stimulating in the heart. Some of the
characteristics of these signals are the
frequency and morphology of their waves.
These components are in the order of just a
few up to 1 mV and their frequency content
within 0.5 and 100 Hz depending on
individual [3]. The morphology and frequency
are analyzed by physicians in order to detect
heart disorders and heart related pathologies.
A typical scalar electrocardiographic lead is
shown in Figure 1, where the significant](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-11-320.jpg)
![CTSP (2016) 16-22 © STM Journals 2016. All Rights Reserved Page 16
Current Trends in Signal Processing
ISSN: 2277-6176(online), ISSN: 2321-4252(print)
Volume 6, Issue 3
www.stmjournals.com
Non-invasive Extraction of Fetal Electrocardiogram and
Maternal Electrocardiogram from Mixed Source Signal
Sai S. Kulkarni*, Supriya O. Rajankar
Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune,
Maharashtra, India
Abstract
This paper is to bring in self-regulating methodology to obtain Fetal Electrocardiogram
(FECG) and Maternal Electrocardiogram (MECG) from the mixed source signal. The
Abdominal Electrocardiogram (AECG) is treated as an input signal to achieve the above-
mentioned goal. FECG and MECG can be differentiated according to the power of a signal.
FECG are weak signals as compared to that of MECG. But, FECG signals are engrossed in
various other interference signals and thus its extraction has gained significance in the
medical field. Various other methods and research work were done in this field. This paper is
focused on non-invasive methods and by implementing independent component analysis.
Various mathematical calculations are used in order to get accurate FECG signal. Then after
‘R’ peaks can be calculated and later fetal heart rate which will help to know the condition of
the fetus in mother’s womb.
Keywords: Abdominal electrocardiogram, blind source separation, fetal electrocardiogram,
independent component analysis, maternal electrocardiogram
INTRODUCTION
An intense research for detecting the condition
of a fetus at the possibility of damage or
demise in the uterus was carried out. Thus,
monitoring the condition of fetus during
pregnancy is one of the important parameters.
The monitoring of a fetus can be done by
invasive as well as non-invasive methods.
Being on the safer side, the researchers,
scientist and the doctors believe in non-
invasive, i.e., harmless methodology to extract
fetal Electrocardiogram (FECG). Useful
information of fetus can be obtained by means
of fetal Electrocardiogram (FECG). For
example, fetal academia, fetal hypoxia, and
fetal acidosis can be diagnosed by fetal heart
rate pattern, duration of ST-segment and
changes observed in QT interval and the T
wave respectively [1].
When the electrodes are placed on the
abdomen of a pregnant woman, abdominal
electrocardiogram (AECG) is obtained. This
AECG consists of FECG as well as MECG in
addition of other noises. Using the concept of
blind source separation, an algorithm named
independent component analysis can be used
to differentiate FECG signals and MECG
signals. FECG signals are of very low voltage
as compared to MECG signals. ICA
(Independent Component Analysis) helps to
extract FECG but not suited for real time
application as it requires high order statistics
and thus prior database is required to carry out
the procedure without any obstacles [2].
PREPROCESSING TECHNIQUES
Before the application of ICA algorithm, some
basic preprocessing techniques are used in
order to improve the efficiency of the output
results.
Let us consider mixed source signal, y as the
n-dimensional vector:
𝑦𝑖(𝑡) = [𝑦1(𝑡), 𝑦2(𝑡), … , 𝑦 𝑁(𝑡)] 𝑇
. Using the ICA
model this is generated as:
𝑦𝑖(𝑡) = 𝐵𝑟𝑖(𝑡) (1)
Where; 𝑟𝑖(𝑡) the vector of n-dimension and its
elements are termed as the sources. While 𝐵𝑛∗𝑛
is termed as unknown mixing matrix. Therefore
the source estimation can be written as:
𝑢(𝑡) = 𝑊𝑥 𝑖
(𝑡) = 𝑊𝐵𝑟𝑖(𝑡) (2)](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-12-320.jpg)
![CTSP (2016) 23-27 © STM Journals 2016. All Rights Reserved Page 23
Current Trends in Signal Processing
ISSN: 2277-6176(online), ISSN: 2321-4252(print)
Volume 6, Issue 3
www.stmjournals.com
Congenital Heart Disease (CHD) Detection Technique
Based on Analysis and Classification of ECG Signal
Pravin Baburao Kamble1,
*, D.T. Ingole2
1
Department of Electronics, Amravati University, Maharashtra, India
2
Department of Electronics, Ram Meghe Institute of Engineering, Amravati, Maharashtra, India
Abstract
As per American Heart Association information, every year 125 babies out of 1000 are born
with congenital heart disease (CHD). It was estimated that 36000 children are live born with
CHD each year in the European Union. Child with CHD may have hole in heart up to 3–5 mm
as small defects and for large defects it may go up to 5–8 mm. Depending upon the size of
hole in the upper or lower chamber of heart shows diseases such as atrial septal defect (ASD),
ventricular septal defect (VSD), patent ductus arteriosus (PDA) and tetralogy of Fallot (TOF).
Child patients with CHD report difficulties in several areas of daily life such as sports, study,
travelling, and driving. It affects the efficiency and functionality of heart. It also affects the
autonomic control of heart rate. The main focus would be to detect CHD in the pediatric
population and preventive measures that can be proposed to improve the quality of life.
Nowadays, we still fill infancy in the analysis of pediatric ECG. In our research work, we
aimed at wave detection of CHD and its ECG analysis with different classification techniques
so that child with CHD can be diagnosed accurately. We then attempted to justify the
recommendation for promising future directions in signal processing and database creation.
Keywords: atrial septal defect (ASD), ventricular septal defect (VSD), patent ductus
arteriosus (PDA), tetralogy of Fallot (TOF)
INTRODUCTION
Heart defects are among the most common
birth defects and lead to cause birth defect-
related deaths [1]. The heart is a pumping
organ and has four chambers. The two upper
chambers are called right atrium (RA) and left
atrium (LA) and the two lower chambers are
called right ventricle (RV) and left ventricle
(LV). The upper chambers are separated by a
wall called interatrial septum and the lower
chambers are separated by another wall called
interventricular septum. Pulmonary artery
takes impure blood to the lungs for
purification and Aorta carries pure rich blood
to the whole body [2].
Congenital heart defect (CHD) simply means
that the heart developed problems since when it
was being formed in the womb. It is a heart
problem that baby is born with. It can include
abnormal development of the heart, the heart
valves, major arteries or combination of these
problems. The atrial septal defect (ASD) is hole
in the upper chamber of heart. The ventricular
septal defect (VSD) is hole in the wall between
the right and left ventricles. The patent ductus
arteriosus (PDA) is an opening between
pulmonary artery and the aorta through which
pure blood intended for the body is directed
back to the lungs. The wave detection of these
diseases and analysis of waves P-QRS-T would
help the pediatric population.
Electrocardiogram (ECG) system helps to
collect data in terms of P-QRS-T wave with
the help of various filters and after collection
of data we can analyze it. Fetal ECG was first
observed by M. Cremer in 1906 [3]. Early
works in this area were performed by using the
galvanometric apparatus of that time, which
were limited by very low amplitude of fetal
signals. As measurement and amplification
techniques improved, fetal ECG (FECG)
became more feasible and popular [4, 5]. In the
1960s, intrauterine electrodes provided SNR
improvement for FECG analysis [6]; but it was
not applicable to the premature heart due to
identification problem. Shortly afterwards, with
the developments in computer science and
signal processing techniques, automatic signal](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-13-320.jpg)
![CTSP (2016) 28-38 © STM Journals 2016. All Rights Reserved Page 28
Current Trends in Signal Processing
ISSN: 2277-6176(online), ISSN: 2321-4252(print)
Volume 6, Issue 3
www.stmjournals.com
Heater Automation Using LabVIEW
N. Dinesh Kumar*, Ch V.B. Aditya Kumar
Department of Electronics and Communication Engineering, Vignan Institute of Technology and
Science, Deshmukhi, Nalgonda, India
Abstract
Water heating system is an age-old tradition being commonly used from domestic sectors to
production sectors; it is a need-based requirement to develop all time and effective water
heating system for use in day-to-day life. With reference to lime lighting the deficiencies in
general water heating systems and improved versions of sensor operated systems, this model
has been designed. The scope of the work is specifically with reference to common household
water heating systems operated using LabVIEW software, facilitating absence of an
individual. Water heaters without control of water level indicator and energy cut off
orientation will cause short circuits in domestic, commercial environments. Intelligent
application of sensors used in the devices will balance the total losses of different kinds and
ensure utmost satisfactory service to the domestic as well as commercial users. In the public
interest and routing out the common man’s water heating problems, the model will deliver the
efficiency oriented water heating systems with cost effectiveness.
Keywords: LabVIEW, heating element, tank, pump, temperature sensor, set point, geyser
INTRODUCTION
Supplying of hot water for domestic as well as
commercial, (i.e., multipurpose) users, by
adopting sensor oriented thermodynamic
heater system without manual supervision,
through which users save time and money.
Though varieties of water heating systems
have emerged in this market, the special
features of this model destine in exhibiting the
auto cutoff of the heater as well as overflow of
water. In addition, the heater will not get
started until there is minimum level in the
geyser [1].
Many water-heating systems are manufactured
based on the concept of continuous supply of
water and current. In the absence of water in
the geyser, if the power supply is made on the
thermostats, coils gets fused off and lot of
damage in the form of short circuit results.
Whereas the latest phenomenal approach like
sensor based auto cut off power supply/water
level indicators, which will save the device as
well as the total power supply system from the
mains. When on commercial use, the impact of
normal water boiling systems without the
advanced techniques will cause human loss
and infrastructure loss due to the blasts, which
occur in the units. By using the automation
techniques in water heating systems, even a
layman can operate the systems without any
extra skills. As the systems are cost effective,
need based automation devices they can
deliver required loads without any power
damage. Thus, anybody can afford to install
this type of sensor-based devices, which are
lifetime dependable and definitely will save
time and money in a longer way.
So this model is constituted on the ideology of
controlling the functions like overflow of tank,
over heating of the system, water level
parameters and auto-cutoff facility. So, the
concept of sensor based heater systems with
unique features like no supply of power to
heater without attaining minimum water levels
and auto cut off of power as well as
temperature of water, will serve the needs of
domestic as well as commercial users. This
type of heaters built with modern scientific
techniques will not only save money but also
save consumption of power and water [2].
IMPLEMENTATION USING
LabVIEW
The model is mainly designed and developed
using the software and hardware components
within the ambit of LabVIEW. LabVIEW is a](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-14-320.jpg)
![CTSP (2016) 39-48 © STM Journals 2016. All Rights Reserved Page 39
Current Trends in Signal Processing
ISSN: 2277-6176(online), ISSN: 2321-4252(print)
Volume 6, Issue 3
www.stmjournals.com
Performance Evaluation of Direction of Arrival
Estimation in Smart Antenna
Raju Dara, Bhongir Sony
Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune,
Maharashtra, India
Abstract
Direction of arrival (DOA) estimation has typically played a key role in signal processing. Its
task is to find the directions impinging on an array antenna to increase the performance of the
received signal. To use DOA estimation methods that are applicable to most environments has
become the key of technique implementation. The traditional algorithms can get superior
performance for DOA estimation in the rich receiving conditions, but they are not fit for
adverse environment such as low SNR, small number of array elements or snapshots, etc. In
order to improve the performance of DOA estimation, the modified method based on wavelet
operator is used. Moreover, the method is applied on DOA estimation algorithm multiple
signal classification (MUSIC) to get new algorithm WMUSIC. Undoubtedly, the wavelet-
based method expands the application range of traditional DOA estimation algorithms and
has widely practical prospects in future. Further results are improved to minimize the errors
in angle estimation by using genetic algorithm.
Keywords: Direction of arrival, MUSIC, SNR
INTRODUCTION
The array signal processing is fast developing
in the last decades [1]. Accurate DOA
estimation will bring many significant
advantages, such as increasing the capacity,
reducing the transmitter power of mobile
terminal, resisting multipath effect, decreasing
interference from outside, and so on [2]. The
various algorithms are proposed successively
in recent years, including capon, high-order
cumulate method, propagator method, min-
norm, MUSIC and ESPRIT, among which
MUSIC is considered to be high resolution and
accuracy method [3]. However, much of the
previous studies show that the performance of
the most DOA estimation algorithms depends
on some factors, such as the number of array
elements and spatial distribution, the number
of snapshots, and signal-to-noise ratio (SNR)
of received array signals [4].
In the light of wavelet transform having the
powerful ability on noise reduction, we
developed a new signal receive model based
on wavelet operator to improve original
methods for estimating DOA. In this report,
we propose modified method called as
WMUSIC, which combines wavelet operator
with MUSIC method to estimate DOA. By
utilizing wavelet transform to filter lots of
noise from the received array signals, DOA of
news de-noised signals can be estimated by
MUSIC method. The modified WMUSIC can
get superior performance even under weak
communication environment. In contrast to the
traditional MUSIC, the modified method can
improve greatly both resolution and accuracy
of DOA estimation. Therefore, the problem of
DOA estimation can be resolved for WMUSIC
under lower SNR.
ARRAY SIGNAL RECEIVED MODEL
Most DOA estimation methods, which are on
signal processing, rely on certain assumptions
made on the received array signals. In the
section, the 2D pattern is used to describe
briefly the model of DOA as follows:
As shown in Figure 1, we considered a
scenario with emitting sources from different
directions with narrowband property, and we
have a linear antenna array with element to
receive each emitting signal.](https://image.slidesharecdn.com/currenttrendsinsignalprocessingvol6issue3-170215044118/85/Current-Trends-in-Signal-Processing-vol-6-issue-3-15-320.jpg)
Current Trends in Signal Processing vol 6 issue 3
- 1. ISSN 2277-6176 (Online) ISSN 2321-4252 (Print) Current Trends in Signal Processing (CTSP) September–December 2016 SJIF: 3.649 www.stmjournals.com STM JOURNALS Scientific Technical Medical
- 2. STM Journals, a strong initiative by Consortium E-Learning Network Private Ltd. (established 2006), was launched in the year 2010 under the support and guidance by our esteemed Editorial and Advisory Board Membersfromrenownedinstitutes. Objectives: Promotion of Scientific, Technical and Medical research. Publication of Original Research/Review, Short Articles and Case Studies through Peer Review process. Publishing Special Issues on Conferences. Preparing online platform for print journals. Empowering the libraries with online and print Journals in Scientific, Technical and Medical domains. Publishing and distribution of books on various subjects in the category of Nanotechnology, Scientific and Technical Writing, and Environment, Health and Safety. SalientFeatures: A bouquet of 100+ Journals that fall under Science, Technical and Medical domains. Employs Open Journals System (OJS)—a journal management and publishing system. The first and one of the fastest growing publication website in India as well as in abroad for its quality and coverage. Rapid online submission and publication of papers, soon after their formal acceptance/finalization. Facilitates linking with the other authors or professionals. Worldwide circulation and visibility. Current Trends in Signal Processing ISSN: 2277-6176 (online), ISSN: 2321-4252 (print) Focus andScopeCovers ElectricalEngineeringandSignaling Systems EngineeringandSignaling AppliedMathematicsandSignaling ControlSystemSignals Telecommunicationtransmissionsignals Analog&digitalsignals Timevaryingmeasurementvalues&sensor data Current Trends in Signal Processing is published (frequency: three times a year) in India by STM Journals (division of Consortium e-Learning Network Private Ltd. Pvt.) The views expressed in the articles do not necessarily reflect of the Publisher. The publisher does not endorse the quality or value of the advertised/sponsored products described therein. Pleaseconsultfullprescribinginformationbeforeissuingaprescriptionfor anyproductsmentionedinthispublication. No part of this publication may be reproduced, stored in retrieval system or transmitted in any from without written permissionof thepublisher. To cite any of the material contained in this Journal, in English or translation, please use the full English reference at the beginningof eacharticle.Toreuseanyofthematerial,pleasecontactSTM Journals (info@stmjournals.com) STM Journals
- 3. STM Journals (division of Consortium e-Learning Network Private Ltd. ) having its Marketing office located at Office No. 4, First Floor, CSC pocket E Market, Mayur Vihar Phase II, New Delhi-110091, India is the Publisher of Journal. Statements and opinions expressed in the Journal reflect the views of the author(s) and are not the opinion of STM Journals unless so stated. Subscription Information and Order: NationalSubscription: Print-Rs 3750/-perJournal( includes3printissues), SingleIssue copypurchase:Rs 1500. Online - Rs 3750/- per Journal inclusive Service Tax ( includes 3 online issues), Single Issue purchase: Rs 1500 inclusiveServiceTax Print+Online-Rs 5000/-perJournalinclusiveServiceTax( includes3print&onlineissues). International Subscription: Online Only- $199, Print Only-$299 (includes 3 print issues) Online + Print-$399 (includes 3 print issues + online access of published back volumes ) To purchase print compilation of back issues please send your query at info@stmjournals.com Subscription must be prepaid. Rates outside of India includes delivery. Prices subject to change without notice. Mode of Payment: At par cheque, Demand draft, and RTGS (payment to be made in favor of Consortium E-Learning Network. Pvt. ltd., payable at Delhi/New Delhi. Online Access Policy A). For Authors: In order to provide maximum citation and wide publicity to the authors work, STM Journals also have Open Access Policy, authors who would like to get their work open access can opt for Optional Open Access publication at nominal cost as follows India, SARC and African Countries: INR 2500 or 100 USD including single hard copy of Author's Journal. Other Countries: USD 200 including single hard copy of Author's Journal. B). For Subscribers: Online access will be activated within 72 hours of receipt of the payment (working days), subject to receipt of correct information on user details/Static IP address of the subscriber. The access will be blocked: If the user requests for the same and furnishes valid reasons for blocking. Due to technical issue. Misuse of the access rights as per the access policy. Advertising and Commercial Reprint Inquiries: STM Journals with wide circulation and visibility offer an excellent media for showcasing/promotion of your products/services and the events-namely, Conferences, Symposia/Seminars etc. These journals have very high potential to deliver the message across the targeted audience regularly with each published issue. The advertisements on bulk subscriptions, gift subscriptions or reprint purchases for distribution etc. are alsoverywelcome. Lost Issue Claims: Please note the following when applying for lost or missing issues: Claims for print copies lost will be honored only after 45 days of the dispatch date and before publication of the next issue as per the frequency. Tracking id for the speed post will be provided to all our subscribers and the claims for the missing Journals will be entertained only with the proofs which will be verified at both the ends. Claims filed due to insufficient (or no notice) of change of address will not be honored. Change of Address of Dispatch should be intimated to STM Journals at least 2 months prior to the dispatch schedule as per the frequency by mentioning subscriber id and the subscription id. Refund requests will not be entertained. Legal Disputes All the legal disputes are subjected to Delhi Jurisdiction only. If you have any questions, please contact the Publication Management Team: info@stmjournals.com; Tel : +91 0120-4781211.
- 4. Gargi Asha Jha Manager (Publications) PUBLICATION MANAGEMENT TEAM Internal Members External Members Bimlesh Lochab Assistant Professor Department of Chemistry School of Natural Sciences, Shiv Nadar University Gautam Buddha Nagar, Uttar Pradesh, India Dr. Rajiv Prakash Professor and Coordinator School of Materials Science and Technology Indian Institute of Technology (BHU), Varanasi Uttar Pradesh, India Dr. Rakesh Kumar Assistant Professor Department of Applied Chemistry BIT Mesra, Patna, Bihar, India Prof. S. Ramaprabhu Alternative Energy and Nanotechnology Technology Laboratory, Department of Physics Indian Institute of Technology, Chennai Tamil Nadu, India Himani Pandey Isha Chandra Senior Associate Editors Dr. Yog Raj Sood Dean (Planning and Development) Professor, Department of Electrical Engineering National Institute of Technology, Hamirpur Himachal Pradesh, India Prof. Chris Cannings Professor, School of Mathematics and Statistics University of Sheffield, Sheffield United Kingdom Dr. D. K. Vijaykumar MS, MCh (Surgical Oncology), Professor and Head Department of Surgical Oncology Amrita Institute of Medical Sciences and Research Centre Ponekkara, Cochin, Kerala, India Dr. Durgadas Naik Associate Professor (Microbiology) Management and Science University, University Drive, Seksyen13 Selangor, Malaysia Prof. José María Luna Ariza Department of Computer Sciences and Numerical Analysis Campus of Rabanales University of Córdoba, Spain Dr. Khaiser Nikam Professor, Library and Information Science Department of Library and Information Science University of Mysore Mysore, India Quaisher J Hossain Senior Editor Group Managing Editor Dr. Archana Mehrotra Managing Director CELNET, Delhi, India Meenakshi Tripathi Shivani Sharma Chairman Mr. Puneet Mehrotra Director Shambhavi Mishra Associate Editors Sugandha Mishra
- 5. Prof. Priyavrat Thareja Director Principal Rayat Institute of Engineering and Information Technology Punjab, India Dr Baldev Raj Director, National Institute of Advanced Studies Indian Institute of Science campus Bangalore Karnataka, India Former Director Indira Gandhi Centre for Atomic Research, Kalpakkam, Tamil Nadu, India Dr. Pankaj Poddar Senior Scientist Physical and Materials Chemistry Division, National Chemical Laboratory Pune, Maharastra India Prof. D. N. Rao Professor and Head Department of Biochemistry All India Institute of Medical Sciences New Delhi, India Dr. Nandini Chatterjee Singh Additional Professor National Brain Research Centre Manesar, Gurgaon Haryana, India Dr. Ashish Runthala Lecturer, Biological Sciences Group Birla Institute of Technology and Science Pilani, Rajasthan, India Dr. Bankim Chandra Ray Professor and Ex-Head of the Department Department of Metallurgical and Materials Engineering National Institute of Technology, Rourkela Odisha, India Prof. Yuwaraj Marotrao Ghugal Professor and Head Department of Applied Mechanics Government College of Engineering Vidyanagar, Karad Maharashtra, India Dr. Hardev Singh Virk Visiting Professor, Department of Physics University of SGGS World University Fatehgarh Sahib, Punjab, India Former Director Research DAV Institute of Engineering and Technology Jallandhar, India Dr. Shrikant Balkisan Dhoot Senior Research Scientist, Reliance Industries Limited, Mumbai, India Former Head (Research and Development) Nurture Earth R&D Pvt Ltd., MIT Campus Beed Bypass Road, Aurangabad Maharashtra, India STM JOURNALS ADVISORY BOARD
- 6. Dr. Rakesh Kumar Assistant Professor Department of Applied Chemistry Birla Institute of Technology Patna, Bihar, India Prof. Subash Chandra Mishra Professor Department of Metallurgical and Materials Engineering National Institute of Technology, Rourkela Odisha, India Dr. Shankargouda Patil Assistant Professor Department of Oral Pathology KLE Society's Institute of Dental Sciences Bangalore, Karnataka, India Prof. Sundara Ramaprabhu Professor Department of Physics Indian Institute of Technology Madras Chennai, Tamil Nadu India Dr. Baskar Kaliyamoorthy Associate Professor Department of Civil Engineering National Institute of Technology, Trichy Tiruchirappalli, Tamil Nadu, India STM JOURNALS ADVISORY BOARD
- 7. Editorial Board Dr Gunamani Jena ME CSE, PhD, FIE, MIEEE, LMISTE, MCSI, India. Dr. Abhijit Mitra Department of EEE, Indian Institute of Technology, Guwahati, India. Dr. Rajiv Kapoor Delhi Technological University, India. Prof. Sumana Gupta Professor, Department of Electrical Engineering, IndianInstitute of Technology, Kanpur, India. Dr. M K Bhuyan Department of Electronics and Electrical Engineering, IIT Guwahati, India. Professor & Head Vinod Kumar Department of Electrical Engineering IIT Roorkee, India.
- 8. It is my privilege to present the print version of the [Volume 6 Issue 3] of our CurrentTrends in Signal Processing, 2016. The intension of CTSP is to create an atmosphere that stimulates vision, research andgrowthintheareaof Signalprocessing. Timely publication, honest communication, comprehensive editing and trust with authors and readers have been the hallmark of our journals. STM Journals provide a platform for scholarly research articles to be published in journals of international standards. STM journals strive to publish qualitypaperinrecordtime,makingitaleaderinserviceandbusiness offerings. The aim and scope of STM Journals is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high level learning, teaching andresearchinalltheScientific,TechnicalandMedicaldomains. Finally, I express my sincere gratitude to our Editorial/ Reviewer board, Authors and publication team for their continued support and invaluable contributions and suggestions in the form of authoring writeups/reviewing and providing constructive comments for the advancement of the journals.With regards to their due continuous support and co-operation, we have been able to publish qualityResearch/Reviewsfindingsfor our customersbase. Ihopeyouwillenjoyreadingthisissue andwewelcomeyourfeedbackonanyaspectof theJournal. Dr.ArchanaMehrotra ManagingDirector STM Journals Director's Desk STM JOURNALS
- 9. 1. Efficient Partial Update Algorithm over Wireless Networks Rupali Dewda, Vijay Barfa 1 2. Elimination of Noise on ECG Signal Using Adaptive Filter ShabnamTahmin, Zeenat Afroze 9 3. Non-invasive Extraction of Fetal Electrocardiogram and Maternal Electrocardiogram from Mixed Source Signal Sai S. Kulkarni, Supriya O. Rajankar 16 4. Congenital Heart Disease (CHD) Detection Technique Based on Analysis and Classification of ECG Signal Pravin Baburao Kamble, D.T. Ingole 23 5. Heater Automation Using LabVIEW N. Dinesh Kumar, Ch V.B. Aditya Kumar 28 6. Performance Evaluation of Direction of Arrival Estimation in Smart Antenna S.S. Jadhav, D.G. Ganage, S.A. Wagh 39 ContentsCurrent Trends in Signal Processing
- 10. CTSP (2016) 1-8 © STM Journals 2016. All Rights Reserved Page 1 Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print) Volume 6, Issue 3 www.stmjournals.com Efficient Partial Update Algorithm over Wireless Networks Rupali Dewda*, Vijay Barfa Department of Electronics and Communication, Rishiraj Institute of Technology, Indore, Madhya Pradesh, India Department of Electronics, Hathway Cable and Datacom Ltd., Indore, Madhya Pradesh, India Abstract Adaptive partial update algorithm is developed based on incremental method. The proposed algorithm applies in real time changing environment. The proposed algorithm responds to linear estimation with nodes in cooperative manner and less number of computations. The algorithm has powerful advantage is that it requires less number of coefficient and reduced computational and communication complexity in wireless sensor network. It is efficient because it has power of solving distributed estimation and optimization by learning mechanism. In wireless sensor networks there are various applications that involve phenomenon in which space parameter are varying like surveillance, environment monitoring, battle field, precision agriculture and medical application. In this paper three algorithms; sequential partial update, stochastic partial update and max partial update are compared in terms of mean square error (MSE). Performance characteristic and complexity analysis of each algorithm are compared with MATLAB simulation. Keywords: Incremental network, Sequential partial update, stochastic partial update, Max partial update, MSE INTRODUCTION A wireless sensor networks (WSNs) composed of an array of sensor nodes, i.e., tiny embedded devices, which are distributed in the geographical area, which collect information or investigate special events and communicate in a wireless manner [1]. The adaptive distributed strategy, which relies on the incremental mode, is the process of cooperation between distinct nodes; these nodes perform local computation and share the result with the neighbouring nodes. The resulting algorithm is cooperative, distributed, and able to respond in real time change in environment [2]. The nodes, which we also interchangeably call agents, consist of at least three main components: process units, sensing devices and a wireless transmit-receive unit. In more advance sensor networks, nodes are also equipped with actuators to take action according to the command issued from a control unit. Due to their vast applications, efficient design and implementation of wireless sensor networks have become an area of current research [2]. Since the nodes in a network function with small and limited battery power and usually nonrenewable resources, it is important to design the networks with less communication among the nodes to estimate the required parameter vector because communication and computation consumes most of the energy [2, 3]. Adaptive distributed strategies with incremental mode of communication focused on reduction in communication complexity among the nodes by restricting a particular node receiving and transmitting to the predefined immediate nodes only instead of every node of the network [4, 5]. In this paper, we study and develop distributed adaptive strategies for monitoring time- varying physical phenomenon in sensor network under real-world limitation and change in environment condition. In this paper, incremental partial update strategies are proposed for weight update,
- 11. CTSP (2016) 9-15 © STM Journals 2016. All Rights Reserved Page 1 Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print) Volume 6, Issue 3 www.stmjournals.com Elimination of Noise on ECG Signal Using Adaptive Filter ShabnamTahmin*, Zeenat Afroze Department of Electrical and Electronics Engineering, American International University-Bangladesh, Bangladesh Abstract There are various biomedical signals present in the human body, by examining these biomedical signal one can check the health condition of a person who is clinically fit or not. Electrocardiogram (ECG) is one of them. ECG plays an important role in the primary diagnosis, prognosis and survival analysis of heart diseases. This ECG signal is corrupted by various noises like power line interference, baseline wandering etc. One way to remove this noise is filtering the signal. This paper will present the performance of adaptive filter on ECG signal. Diseases can be found by mixing power line interference with the ECG signal. We have used the advanced adaptive filtering technique with Least Mean Square Algorithm for the removal of power line interference from the ECG signal. Also, we have changed different parameter of adaptive filter and we analyzed the performance of algorithm in terms of Signal to Noise Ratio (SNR) improvement. Keywords: ECG Signal, adaptive filter, least mean square (LMS), signal to noise ratio (SNR) INTRODUCTION The electrocardiograph (ECG) is an instrument, which records the electrical activity of the heart. A cleaned ECG signal provides necessary information about the electrophysiology of the heart diseases and ischemic changes that may occur. It provides valuable information about the functional aspects of the heart and cardiovascular system. The ECG works mostly by detecting and amplifying the tiny electrical changes on the skin that are caused when the heart muscle "depolarizes" during each heartbeat. This is detected as tiny rises and falls in the voltage between two electrodes placed either side of the heart, which is displayed as a wavy line either on a screen or on a paper [1]. This display indicates the overall rhythm of the heart and weaknesses in different parts of the heart muscle, so it is very important to get the ECG signal clean and free from noise [1]. ECG signal generated from human body are often very weak so as to be easily covered by background noise. The noise in the ECG signals occur due to various reasons like electromagnetic interference due to ubiquitous supply lines and plugs, movement of patient, signals generated by other organs and impedance mismatching between electrodes [2]. Hence, the ECG signals can be corrupted by various types of noises such as Power line interference, Electrode contact noise, Motion artifact, Muscle contraction, Base line drift, Instrumental noise generated by electronic devices [2]. ECG signal has frequency range from 0.5 to 80 Hz and power line interference introduces 50 to 60 Hz frequency component in that signal which is the major cause of corruption of ECG. Various methods have been employed for the removal of power line interference from ECG signals. One of them is using an adaptive filter. SIGNIFICANT FEATURES OF ECG WAVEFORM ECG records carrier information about abnormalities or responses to certain stimulating in the heart. Some of the characteristics of these signals are the frequency and morphology of their waves. These components are in the order of just a few up to 1 mV and their frequency content within 0.5 and 100 Hz depending on individual [3]. The morphology and frequency are analyzed by physicians in order to detect heart disorders and heart related pathologies. A typical scalar electrocardiographic lead is shown in Figure 1, where the significant
- 12. CTSP (2016) 16-22 © STM Journals 2016. All Rights Reserved Page 16 Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print) Volume 6, Issue 3 www.stmjournals.com Non-invasive Extraction of Fetal Electrocardiogram and Maternal Electrocardiogram from Mixed Source Signal Sai S. Kulkarni*, Supriya O. Rajankar Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune, Maharashtra, India Abstract This paper is to bring in self-regulating methodology to obtain Fetal Electrocardiogram (FECG) and Maternal Electrocardiogram (MECG) from the mixed source signal. The Abdominal Electrocardiogram (AECG) is treated as an input signal to achieve the above- mentioned goal. FECG and MECG can be differentiated according to the power of a signal. FECG are weak signals as compared to that of MECG. But, FECG signals are engrossed in various other interference signals and thus its extraction has gained significance in the medical field. Various other methods and research work were done in this field. This paper is focused on non-invasive methods and by implementing independent component analysis. Various mathematical calculations are used in order to get accurate FECG signal. Then after ‘R’ peaks can be calculated and later fetal heart rate which will help to know the condition of the fetus in mother’s womb. Keywords: Abdominal electrocardiogram, blind source separation, fetal electrocardiogram, independent component analysis, maternal electrocardiogram INTRODUCTION An intense research for detecting the condition of a fetus at the possibility of damage or demise in the uterus was carried out. Thus, monitoring the condition of fetus during pregnancy is one of the important parameters. The monitoring of a fetus can be done by invasive as well as non-invasive methods. Being on the safer side, the researchers, scientist and the doctors believe in non- invasive, i.e., harmless methodology to extract fetal Electrocardiogram (FECG). Useful information of fetus can be obtained by means of fetal Electrocardiogram (FECG). For example, fetal academia, fetal hypoxia, and fetal acidosis can be diagnosed by fetal heart rate pattern, duration of ST-segment and changes observed in QT interval and the T wave respectively [1]. When the electrodes are placed on the abdomen of a pregnant woman, abdominal electrocardiogram (AECG) is obtained. This AECG consists of FECG as well as MECG in addition of other noises. Using the concept of blind source separation, an algorithm named independent component analysis can be used to differentiate FECG signals and MECG signals. FECG signals are of very low voltage as compared to MECG signals. ICA (Independent Component Analysis) helps to extract FECG but not suited for real time application as it requires high order statistics and thus prior database is required to carry out the procedure without any obstacles [2]. PREPROCESSING TECHNIQUES Before the application of ICA algorithm, some basic preprocessing techniques are used in order to improve the efficiency of the output results. Let us consider mixed source signal, y as the n-dimensional vector: 𝑦𝑖(𝑡) = [𝑦1(𝑡), 𝑦2(𝑡), … , 𝑦 𝑁(𝑡)] 𝑇 . Using the ICA model this is generated as: 𝑦𝑖(𝑡) = 𝐵𝑟𝑖(𝑡) (1) Where; 𝑟𝑖(𝑡) the vector of n-dimension and its elements are termed as the sources. While 𝐵𝑛∗𝑛 is termed as unknown mixing matrix. Therefore the source estimation can be written as: 𝑢(𝑡) = 𝑊𝑥 𝑖 (𝑡) = 𝑊𝐵𝑟𝑖(𝑡) (2)
- 13. CTSP (2016) 23-27 © STM Journals 2016. All Rights Reserved Page 23 Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print) Volume 6, Issue 3 www.stmjournals.com Congenital Heart Disease (CHD) Detection Technique Based on Analysis and Classification of ECG Signal Pravin Baburao Kamble1, *, D.T. Ingole2 1 Department of Electronics, Amravati University, Maharashtra, India 2 Department of Electronics, Ram Meghe Institute of Engineering, Amravati, Maharashtra, India Abstract As per American Heart Association information, every year 125 babies out of 1000 are born with congenital heart disease (CHD). It was estimated that 36000 children are live born with CHD each year in the European Union. Child with CHD may have hole in heart up to 3–5 mm as small defects and for large defects it may go up to 5–8 mm. Depending upon the size of hole in the upper or lower chamber of heart shows diseases such as atrial septal defect (ASD), ventricular septal defect (VSD), patent ductus arteriosus (PDA) and tetralogy of Fallot (TOF). Child patients with CHD report difficulties in several areas of daily life such as sports, study, travelling, and driving. It affects the efficiency and functionality of heart. It also affects the autonomic control of heart rate. The main focus would be to detect CHD in the pediatric population and preventive measures that can be proposed to improve the quality of life. Nowadays, we still fill infancy in the analysis of pediatric ECG. In our research work, we aimed at wave detection of CHD and its ECG analysis with different classification techniques so that child with CHD can be diagnosed accurately. We then attempted to justify the recommendation for promising future directions in signal processing and database creation. Keywords: atrial septal defect (ASD), ventricular septal defect (VSD), patent ductus arteriosus (PDA), tetralogy of Fallot (TOF) INTRODUCTION Heart defects are among the most common birth defects and lead to cause birth defect- related deaths [1]. The heart is a pumping organ and has four chambers. The two upper chambers are called right atrium (RA) and left atrium (LA) and the two lower chambers are called right ventricle (RV) and left ventricle (LV). The upper chambers are separated by a wall called interatrial septum and the lower chambers are separated by another wall called interventricular septum. Pulmonary artery takes impure blood to the lungs for purification and Aorta carries pure rich blood to the whole body [2]. Congenital heart defect (CHD) simply means that the heart developed problems since when it was being formed in the womb. It is a heart problem that baby is born with. It can include abnormal development of the heart, the heart valves, major arteries or combination of these problems. The atrial septal defect (ASD) is hole in the upper chamber of heart. The ventricular septal defect (VSD) is hole in the wall between the right and left ventricles. The patent ductus arteriosus (PDA) is an opening between pulmonary artery and the aorta through which pure blood intended for the body is directed back to the lungs. The wave detection of these diseases and analysis of waves P-QRS-T would help the pediatric population. Electrocardiogram (ECG) system helps to collect data in terms of P-QRS-T wave with the help of various filters and after collection of data we can analyze it. Fetal ECG was first observed by M. Cremer in 1906 [3]. Early works in this area were performed by using the galvanometric apparatus of that time, which were limited by very low amplitude of fetal signals. As measurement and amplification techniques improved, fetal ECG (FECG) became more feasible and popular [4, 5]. In the 1960s, intrauterine electrodes provided SNR improvement for FECG analysis [6]; but it was not applicable to the premature heart due to identification problem. Shortly afterwards, with the developments in computer science and signal processing techniques, automatic signal
- 14. CTSP (2016) 28-38 © STM Journals 2016. All Rights Reserved Page 28 Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print) Volume 6, Issue 3 www.stmjournals.com Heater Automation Using LabVIEW N. Dinesh Kumar*, Ch V.B. Aditya Kumar Department of Electronics and Communication Engineering, Vignan Institute of Technology and Science, Deshmukhi, Nalgonda, India Abstract Water heating system is an age-old tradition being commonly used from domestic sectors to production sectors; it is a need-based requirement to develop all time and effective water heating system for use in day-to-day life. With reference to lime lighting the deficiencies in general water heating systems and improved versions of sensor operated systems, this model has been designed. The scope of the work is specifically with reference to common household water heating systems operated using LabVIEW software, facilitating absence of an individual. Water heaters without control of water level indicator and energy cut off orientation will cause short circuits in domestic, commercial environments. Intelligent application of sensors used in the devices will balance the total losses of different kinds and ensure utmost satisfactory service to the domestic as well as commercial users. In the public interest and routing out the common man’s water heating problems, the model will deliver the efficiency oriented water heating systems with cost effectiveness. Keywords: LabVIEW, heating element, tank, pump, temperature sensor, set point, geyser INTRODUCTION Supplying of hot water for domestic as well as commercial, (i.e., multipurpose) users, by adopting sensor oriented thermodynamic heater system without manual supervision, through which users save time and money. Though varieties of water heating systems have emerged in this market, the special features of this model destine in exhibiting the auto cutoff of the heater as well as overflow of water. In addition, the heater will not get started until there is minimum level in the geyser [1]. Many water-heating systems are manufactured based on the concept of continuous supply of water and current. In the absence of water in the geyser, if the power supply is made on the thermostats, coils gets fused off and lot of damage in the form of short circuit results. Whereas the latest phenomenal approach like sensor based auto cut off power supply/water level indicators, which will save the device as well as the total power supply system from the mains. When on commercial use, the impact of normal water boiling systems without the advanced techniques will cause human loss and infrastructure loss due to the blasts, which occur in the units. By using the automation techniques in water heating systems, even a layman can operate the systems without any extra skills. As the systems are cost effective, need based automation devices they can deliver required loads without any power damage. Thus, anybody can afford to install this type of sensor-based devices, which are lifetime dependable and definitely will save time and money in a longer way. So this model is constituted on the ideology of controlling the functions like overflow of tank, over heating of the system, water level parameters and auto-cutoff facility. So, the concept of sensor based heater systems with unique features like no supply of power to heater without attaining minimum water levels and auto cut off of power as well as temperature of water, will serve the needs of domestic as well as commercial users. This type of heaters built with modern scientific techniques will not only save money but also save consumption of power and water [2]. IMPLEMENTATION USING LabVIEW The model is mainly designed and developed using the software and hardware components within the ambit of LabVIEW. LabVIEW is a
- 15. CTSP (2016) 39-48 © STM Journals 2016. All Rights Reserved Page 39 Current Trends in Signal Processing ISSN: 2277-6176(online), ISSN: 2321-4252(print) Volume 6, Issue 3 www.stmjournals.com Performance Evaluation of Direction of Arrival Estimation in Smart Antenna Raju Dara, Bhongir Sony Department of Electronics and Telecommunication, Sinhgad College of Engineering, Pune, Maharashtra, India Abstract Direction of arrival (DOA) estimation has typically played a key role in signal processing. Its task is to find the directions impinging on an array antenna to increase the performance of the received signal. To use DOA estimation methods that are applicable to most environments has become the key of technique implementation. The traditional algorithms can get superior performance for DOA estimation in the rich receiving conditions, but they are not fit for adverse environment such as low SNR, small number of array elements or snapshots, etc. In order to improve the performance of DOA estimation, the modified method based on wavelet operator is used. Moreover, the method is applied on DOA estimation algorithm multiple signal classification (MUSIC) to get new algorithm WMUSIC. Undoubtedly, the wavelet- based method expands the application range of traditional DOA estimation algorithms and has widely practical prospects in future. Further results are improved to minimize the errors in angle estimation by using genetic algorithm. Keywords: Direction of arrival, MUSIC, SNR INTRODUCTION The array signal processing is fast developing in the last decades [1]. Accurate DOA estimation will bring many significant advantages, such as increasing the capacity, reducing the transmitter power of mobile terminal, resisting multipath effect, decreasing interference from outside, and so on [2]. The various algorithms are proposed successively in recent years, including capon, high-order cumulate method, propagator method, min- norm, MUSIC and ESPRIT, among which MUSIC is considered to be high resolution and accuracy method [3]. However, much of the previous studies show that the performance of the most DOA estimation algorithms depends on some factors, such as the number of array elements and spatial distribution, the number of snapshots, and signal-to-noise ratio (SNR) of received array signals [4]. In the light of wavelet transform having the powerful ability on noise reduction, we developed a new signal receive model based on wavelet operator to improve original methods for estimating DOA. In this report, we propose modified method called as WMUSIC, which combines wavelet operator with MUSIC method to estimate DOA. By utilizing wavelet transform to filter lots of noise from the received array signals, DOA of news de-noised signals can be estimated by MUSIC method. The modified WMUSIC can get superior performance even under weak communication environment. In contrast to the traditional MUSIC, the modified method can improve greatly both resolution and accuracy of DOA estimation. Therefore, the problem of DOA estimation can be resolved for WMUSIC under lower SNR. ARRAY SIGNAL RECEIVED MODEL Most DOA estimation methods, which are on signal processing, rely on certain assumptions made on the received array signals. In the section, the 2D pattern is used to describe briefly the model of DOA as follows: As shown in Figure 1, we considered a scenario with emitting sources from different directions with narrowband property, and we have a linear antenna array with element to receive each emitting signal.
- 16. ISSN 2277-6176 (Online) ISSN 2321-4252 (Print) Current Trends in Signal Processing (CTSP) September–December 2016 SJIF: 3.649 www.stmjournals.com STM JOURNALS Scientific Technical Medical