Probabilistic Framework for the Positioning Of a Vehicle in a Combined Indoor-Outdoor Scenario

Abstract

The development in technology has given us all sophistications but equal amounts of threats too. This has brought us an urge to bring a complete security system that monitors an object continuously. Consider a situation where a cargo vehicle carrying valuable material is moving in an area using GPS (an outdoor sensor) we can monitor it but the actual problem arises when its movement involves both indoor (with in the industry) and outdoor because GPS has its limitations in indoor environment. Hence it is essential to have an additional sensor that would enable us a continuous monitoring /tracking with out cutoff of the signal. In this paper we bring out a solution by combining Ultra wide band (UWB) with GPS sensory information which eliminates the limitations of conventional tracking methods in mixed scenario(indoor and outdoor) The same method finds application in mobile robots, monitoring a person on grounds of security, etc.

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Probabilistic Framework for the Positioning
Of a Vehicle in a Combined Indoor-Outdoor
Scenario
S.Silvia Rachel
1
, E.Edinda Christy
2
, K.Mala
3
, Christo Ananth
4
P.G. Scholars, Department of M.E. Communication Systems,
Francis Xavier Engineering College, Tirunelveli
1,2,3
Associate Professor, Department of ECE,
Francis Xavier Engineering College, Tirunelveli
4
ABSTRACT
The development in technology has given
us all sophistications but equal amounts of
threats too. This has brought us an urge to
bring a complete security system that
monitors an object continuously. Consider
a situation where a cargo vehicle carrying
valuable material is moving in an area
using GPS (an outdoor sensor) we can
monitor it but the actual problem arises
when its movement involves both indoor
(with in the industry) and outdoor because
GPS has its limitations in indoor
environment. Hence it is essential to have
an additional sensor that would enable us a
continuous monitoring /tracking with out
cutoff of the signal. In this paper we bring
out a solution by combining Ultra wide
band (UWB) with GPS sensory information
which eliminates the limitations of
conventional tracking methods in mixed
scenario(indoor and outdoor) The same
method finds application in mobile robots,
monitoring a person on grounds of
security, etc.
INTRODUCTION
Vehicle localization has been often
addressed separately for indoor and outdoor
environments. The main differences
between both cases come from the different
performances of the commonly employed
sensors: typically, indoors sensors (laser
range finders, radio beacons, etc) are more
robust and provide more accurate
positioning than outdoor sensors, like for
example, GPS. However, in those
applications in which vehicle localization
has to be approached in a mixed scenario,
positioning methods relying on both
technologies should coexist. Furthermore,
the transitions between indoor outdoor areas,
where data from both type of sensors are
available, should be managed coherently and
exploited as a whole.

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This paper describes the application of the
Particle Filters as a probabilistic framework
to cope with vehicle localization where
UWB or GPS positioning information is
available, either separately or jointly, as for
example in automatic guidance of transport
vehicles among industrial facilities.
Probabilistic approaches for the
positioning problem are based on the
estimation of a posterior probability
distribution within the space of possible
positions of the vehicle. They provide near-
optimal results under certain independence
assumptions and a given knowledge on the
initial localization. One of such mechanism
is the well known Kalman filter, which
forces the uncertainty to be Gaussian
distributed.
Different variations have been
proposed to deal with this limitation, for
example multihypothesis Kalman filters and
Markov Localization. Among the
markovian methods, it is remarkable the
Monte Carlo localization algorithms (MCL),
also called Particle Filters or Condensation
Algorithms , which work by representing the
posterior estimation of the possible positions
by a set of weighted samples, or particles.
This approach exhibits the following
advantages:
They have the ability to work with almost
arbitrary sensor characteristics, motion
dynamics, and noise distributions, even non-
linearities.
They can represent several position
hypotheses simultaneously.
Computational resources are well focused,
since these methods sample proportionally
to the posterior distribution.
Particle filters are easy to implement.
They provide a suitable framework for the
fusion of sensory information provided by
different devices.
They have also some disadvantages:
Since the prediction is supported by
particles, that is, by samples, a vehicle with
a well-know position can loose its track
because none of the generated samples is
near enough to the true position.
Paradoxically, too accurate sensors
cause the impoverishment of the sample
space. Christo Ananth et al. [1] proposed a
system about Efficient Sensor Network for
Vehicle Security. Today vehicle theft rate is
very high, greater challenges are coming
from thieves thus tracking/ alarming systems
are being deployed with an increasingly
popularity .As per as security is concerned
today most of the vehicles are running on
the LPG so it is necessary to monitor any
leakage or level of LPG in order to provide
safety to passenger. Also in this fast running
world everybody is in hurry so it is required
to provide fully automated maintenance
system to make the journey of the passenger
safe, comfortable and economical. To make
the system more intelligent and advanced it
is required to introduce some important
developments that can help to promote not
only the luxurious but also safety drive to
the owner. The system “Efficient Sensor
Network for Vehicle Security”, introduces a
new trend in automobile industry. Christo
Ananth et al. [2] discussed about Intelligent
Sensor Network for Vehicle Maintenance
System. Modern automobiles are no longer
mere mechanical devices; they are
pervasively monitored through various

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sensor networks & using integrated circuits
and microprocessor based design and
control techniques while this transformation
has driven major advancements in efficiency
and safety.
In the existing system the stress was
given on the safety of the vehicle,
modification in the physical structure of the
vehicle but the proposed system introduces
essential concept in the field of automobile
industry. It is an interfacing of the advanced
technologies like Embedded Systems and
the Automobile world. This “Intelligent
Sensor Network for Vehicle Maintenance
System” is best suitable for vehicle security
as well as for vehicle’s maintenance. Further
it also supports advanced feature of GSM
module interfacing. Through this concept in
case of any emergency or accident the
system will automatically sense and records
the different parameters like LPG gas level,
Engine Temperature, present speed and etc.
so that at the time of investigation this
parameters may play important role to find
out the possible reasons of the accident.
Further, in case of accident & in case
of stealing of vehicle GSM module will send
SMS to the Police, insurance company as
well as to the family members. Christo
Ananth et al. [3] discussed about an eye
blinking sensor. Nowadays heart attack
patients are increasing day by day."Though
it is tough to save the heart attack patients,
we can increase the statistics of saving the
life of patients & the life of others whom
they are responsible for. The main design of
this project is to track the heart attack of
patients who are suffering from any attacks
during driving and send them a medical
need & thereby to stop the vehicle to ensure
that the persons along them are safe from
accident. Here, an eye blinking sensor is
used to sense the blinking of the eye. spO2
sensor checks the pulse rate of the patient.
Both are connected to micro controller.If
eye blinking gets stopped then the signal is
sent to the controller to make an alarm
through the buffer. If spO2 sensor senses a
variation in pulse or low oxygen content in
blood, it may results in heart failure and
therefore the controller stops the motor of
the vehicle. Then Tarang F4 transmitter is
used to send the vehicle number & the
mobile number of the patient to a nearest
medical station within 25 km for medical
aid. The pulse rate monitored via LCD .
The Tarang F4 receiver receives the
signal and passes through controller and the
number gets displayed in the LCD screen
and an alarm is produced through a buzzer
as soon the signal is received. Christo
Ananth et al. [4] discussed about a system,
GSM based AMR has low infrastructure
cost and it reduces man power. The system
is fully automatic, hence the probability of
error is reduced. The data is highly secured
and it not only solve the problem of
traditional meter reading system but also
provides additional features such as power
disconnection, reconnection and the concept
of power management. The database stores
the current month and also all the previous
month data for the future use. Hence the
system saves a lot amount of time and
energy. Due to the power fluctuations, there
might be a damage in the home appliances.
Hence to avoid such damages and to
protect the appliances, the voltage

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controlling method can be implemented.
Christo Ananth et al. [5] discussed about a
system, in this project an automatic meter
reading system is designed using GSM
Technology. The embedded micro controller
is interfaced with the GSM Module. This
setup is fitted in home. The energy meter is
attached to the micro controller. This
controller reads the data from the meter
output and transfers that data to GSM
Module through the serial port. The
embedded micro controller has the
knowledge of sending message to the system
through the GSM module. Another system is
placed in EB office, which is the authority
office. When they send “unit request” to the
microcontroller which is placed in home.
Then the unit value is sent to the EB office
PC through GSM module. According to the
readings, the authority officer will send the
information about the bill to the customer. If
the customer doesn’t pay bill on-time, the
power supply to the corresponding home
power unit is cut, by sending the command
through to the microcontroller. Once the
payment of bill is done the power supply is
given to the customer. Power management
concept is introduced, in which during the
restriction mode only limited amount of
power supply can be used by the customer.
Christo Ananth et al. [6] proposed a method
in which the minimization is per-formed in a
sequential manner by the fusion move
algorithm that uses the QPBO min-cut
algorithm. Multi-shape GCs are proven to be
more beneficial than single-shape GCs.
Hence, the segmentation methods are
validated by calculating statistical measures.
The false positive (FP) is reduced and
sensitivity and specificity improved by
multiple MTANN. Christo Ananth et al. [7]
proposed a system, this system has
concentrated on finding a fast and
interactive segmentation method for liver
and tumor segmentation. In the pre-
processing stage, Mean shift filter is applied
to CT image process and statistical
thresholding method is applied for reducing
processing area with improving detections
rate. In the Second stage, the liver region has
been segmented using the algorithm of the
proposed method. Next, the tumor region
has been segmented using Geodesic Graph
cut method. Results show that the proposed
method is less prone to shortcutting than
typical graph cut methods while being less
sensitive to seed placement and better at
edge localization than geodesic methods.
This leads to increased segmentation
accuracy and reduced effort on the part of
the user. Finally Segmented Liver and
Tumor Regions were shown from the
abdominal Computed Tomographic image.
Christo Ananth et al. [8] proposed a system,
in which a predicate is defined for
measuring the evidence for a boundary
between two regions using Geodesic Graph-
based representation of the image. The
algorithm is applied to image segmentation
using two different kinds of local
neighborhoods in constructing the graph.
Liver and hepatic tumor segmentation can
be automatically processed by the Geodesic
graph-cut based method. This system has
concentrated on finding a fast and
interactive segmentation method for liver
and tumor segmentation. In the
preprocessing stage, the CT image process is

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carried over with mean shift filter and
statistical thresholding method for reducing
processing area with improving detections
rate. Second stage is liver segmentation; the
liver region has been segmented using the
algorithm of the proposed method. The next
stage tumor segmentation also followed the
same steps.
Finally the liver and tumor regions
are separately segmented from the computer
tomography image. Christo Ananth et al. [9]
proposed a system in which the cross-
diamond search algorithm employs two
diamond search patterns (a large and small)
and a halfway-stop technique. It finds small
motion vectors with fewer search points than
the DS algorithm while maintaining similar
or even better search quality. The efficient
Three Step Search (E3SS) algorithm
requires less computation and performs
better in terms of PSNR. Modified objected
block-base vector search algorithm (MOBS)
fully utilizes the correlations existing in
motion vectors to reduce the computations.
Fast Objected - Base Efficient (FOBE)
Three Step Search algorithm combines
E3SS and MOBS. By combining these two
existing algorithms CDS and MOBS, a new
algorithm is proposed with reduced
computational complexity without
degradation in quality. Christo Ananth et al.
[10] proposed a system in which this study
presented the implementation of two fully
automatic liver and tumors segmentation
techniques and their comparative
assessment. The described adaptive
initialization method enabled fully automatic
liver surface segmentation with both GVF
active contour and graph-cut techniques,
demonstrating the feasibility of two different
approaches. The comparative assessment
showed that the graph-cut method provided
superior results in terms of accuracy and did
not present the described main limitations
related to the GVF method. The proposed
image processing method will improve
computerized CT-based 3-D visualizations
enabling noninvasive diagnosis of hepatic
tumors. The described imaging approach
might be valuable also for monitoring of
postoperative outcomes through CT-
volumetric assessments.
Processing time is an important
feature for any computer-aided diagnosis
system, especially in the intra-operative
phase. Christo Ananth et al. [11] proposed a
system in which an automatic anatomy
segmentation method is proposed which
effectively combines the Active Appearance
Model, Live Wire and Graph Cut (ALG)
ideas to exploit their complementary
strengths. It consists of three main parts:
model building, initialization, and
delineation. For the initialization
(recognition) part, a pseudo strategy is
employed and the organs are segmented
slice by slice via the OAAM (Oriented
Active Appearance method). The purpose of
initialization is to provide rough object
localization and shape constraints for a latter
GC method, which will produce refined
delineation. It is better to have a fast and
robust method than a slow and more
accurate technique for initialization. Christo
Ananth et al. [12] proposed a system which
uses intermediate features of maximum
overlap wavelet transform (IMOWT) as a
pre-processing step. The coefficients derived

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from IMOWT are subjected to 2D histogram
Grouping. This method is simple, fast and
unsupervised. 2D histograms are used to
obtain Grouping of color image. This
Grouping output gives three segmentation
maps which are fused together to get the
final segmented output. This method
produces good segmentation results when
compared to the direct application of 2D
Histogram Grouping.
IMOWT is the efficient transform in
which a set of wavelet features of the same
size of various levels of resolutions and
different local window sizes for different
levels are used. IMOWT is efficient because
of its time effectiveness, flexibility and
translation invariance which are useful for
good segmentation results. Christo Ananth
et al. [13] proposed a system in which OWT
extracts wavelet features which give a good
separation of different patterns. Moreover
the proposed algorithm uses morphological
operators for effective segmentation. From
the qualitative and quantitative results, it is
concluded that our proposed method has
improved segmentation quality and it is
reliable, fast and can be used with reduced
computational complexity than direct
applications of Histogram Clustering. The
main advantage of this method is the use of
single parameter and also very faster. While
comparing with five color spaces,
segmentation scheme produces results
noticeably better in RGB color space
compared to all other color spaces. Christo
Ananth et al. [14] presented an automatic
segmentation method which effectively
combines Active Contour Model, Live Wire
method and Graph Cut approach (CLG).
The aim of Live wire method is to provide
control to the user on segmentation process
during execution. Active Contour Model
provides a statistical model of object shape
and appearance to a new image which are
built during a training phase. In the graph
cut technique, each pixel is represented as a
node and the distance between those nodes
is represented as edges. In graph theory, a
cut is a partition of the nodes that divides the
graph into two disjoint subsets. For
initialization, a pseudo strategy is employed
and the organs are segmented slice by slice
through the OACAM (Oriented Active
Contour Appearance Model). Initialization
provides rough object localization and shape
constraints which produce refined
delineation.
This method is tested with different
set of images including CT and MR images
especially 3D images and produced perfect
segmentation results. Christo Ananth et al.
[15] proposed a work, in this work, a
framework of feature distribution scheme is
proposed for object matching. In this
approach, information is distributed in such
a way that each individual node maintains
only a small amount of information about
the objects seen by the network.
Nevertheless, this amount is sufficient to
efficiently route queries through the network
without any degradation of the matching
performance. Digital image processing
approaches have been investigated to
reconstruct a high resolution image from
aliased low resolution images. The accurate
registrations between low resolution images
are very important to the reconstruction of a
high resolution image. The proposed feature

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distribution scheme results in far lower
network traffic load.
To achieve the maximum
performance as with the full distribution of
feature vectors, a set of requirements
regarding abstraction, storage space,
similarity metric and convergence has been
proposed to implement this work in C++ and
QT. Christo Ananth et al. [16] discussed
about an important work which presents a
metal detecting robot using RF
communication with wireless audio and
video transmission and it is designed and
implemented with Atmel 89C51 MCU in
embedded system domain. The robot is
moved in particular direction using switches
and the images are captured along with the
audio and images are watched on the
television .Experimental work has been
carried out carefully. The result shows that
higher efficiency is indeed achieved using
the embedded system. The proposed method
is verified to be highly beneficial for the
security purpose and industrial purpose. The
mine sensor worked at a constant speed
without any problem despite its extension,
meeting the specification required for the
mine detection sensor. It contributed to the
improvement of detection rate, while
enhancing the operability as evidenced by
completion of all the detection work as
scheduled. The tests demonstrated that the
robot would not pose any performance
problem for installation of the mine
detection sensor. On the other hand,
however, the tests also clearly indicated
areas where improvement, modification,
specification change and additional features
to the robot are required to serve better for
the intended purpose. Valuable data and
hints were obtained in connection with such
issues as control method with the mine
detection robot tilted, merits and drawbacks
of mounting the sensor, cost, handling the
cable between the robot and support vehicle,
maintainability, serviceability and easiness
of adjustments.
These issues became identified as a
result of our engineers conducting both the
domestic tests and the overseas tests by
themselves, and in this respect the findings
were all the more practical. Christo Ananth
et al. [17] discussed about Vision based Path
Planning and Tracking control using Mobile
Robot. This paper proposes a novel
methodology for autonomous mobile robot
navigation utilizing the concept of tracking
control. Vision-based path planning and
subsequent tracking are performed by
utilizing proposed stable adaptive state
feedback fuzzy tracking controllers designed
using the Lyapunov theory and particle-
swarm-optimization (PSO)-based hybrid
approaches. The objective is to design two
self-adaptive fuzzy controllers, for x-
direction and y-direction movements,
optimizing both its structures and free
parameters, such that the designed
controllers can guarantee desired stability
and, simultaneously, can provide
satisfactory tracking performance for the
vision-based navigation of mobile robot.
The design methodology for the
controllers simultaneously utilizes the global
search capability of PSO and
Lyapunovtheory-based local search method,
thus providing a high degree of automation.
Two different variants of hybrid approaches

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have been employed in this work. The
proposed schemes have been implemented
in both simulation and experimentations
with a real robot, and the results demonstrate
the usefulness of the proposed concept.
Christo Ananth et al. [18] discussed about a
model, a new model is designed for
boundary detection and applied it to object
segmentation problem in medical images.
Our edge following technique incorporates a
vector image model and the edge map
information. The proposed technique was
applied to detect the object boundaries in
several types of noisy images where the ill-
defined edges were encountered. The
proposed techniques performances on object
segmentation and computation time were
evaluated by comparing with the popular
methods, i.e., the ACM, GVF snake models.
Several synthetic noisy images were created
and tested.
The method is successfully tested in
different types of medical images including
aortas in cardiovascular MR images, and
heart in CT images. Christo Ananth et al.
[19] discussed about the issue of intuitive
frontal area/foundation division in still
pictures is of awesome down to earth
significance in picture altering. They
maintain a strategic distance from the limit
length predisposition of chart cut strategies
and results in expanded affectability to seed
situation. Another proposed technique for
completely programmed handling structures
is given taking into account Graph-cut and
Geodesic Graph cut calculations. This paper
addresses the issue of dividing liver and
tumor locales from the stomach CT pictures.
The absence of edge displaying in geodesic
or comparable methodologies confines their
capacity to exactly restrict object limits,
something at which chart cut strategies by
and large exceed expectations. A predicate
is characterized for measuring the
confirmation for a limit between two locales
utilizing Geodesic Graph-based
representation of the picture. The calculation
is connected to picture division utilizing two
various types of nearby neighborhoods in
building the chart. Liver and hepatic tumor
division can be naturally prepared by the
Geodesic chart cut based strategy. This
framework has focused on finding a quick
and intuitive division strategy for liver and
tumor division.
In the pre-handling stage, Mean
movement channel is connected to CT
picture process and factual thresholding
technique is connected for diminishing
preparing zone with enhancing discoveries
rate. In the Second stage, the liver area has
been divided utilizing the calculation of the
proposed strategy. Next, the tumor district
has been portioned utilizing Geodesic Graph
cut strategy. Results demonstrate that the
proposed strategy is less inclined to
shortcutting than run of the mill diagram cut
techniques while being less delicate to seed
position and preferable at edge restriction
over geodesic strategies. This prompts
expanded division exactness and decreased
exertion with respect to the client. At long
last Segmented Liver and Tumor Regions
were appeared from the stomach Computed
Tomographic picture.
Christo Ananth et al.
[20
] discussed about efficient content-based
medical image retrieval, dignified according
to the Patterns for Next generation Database

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systems (PANDA) framework for pattern
representation and management. The
proposed scheme use 2-D Wavelet
Transform that involves block-based low-
level feature extraction from images. An
expectation–maximization algorithm is used
to cluster the feature space to form higher
level, semantically meaningful patterns.
Then, the 2-component property of PANDA
is exploited: the similarity between two
clusters is estimated as a function of the
similarity of both their structures and the
measure components. Experiments were
performed on a large set of reference
radiographic images, using different kinds of
features to encode the low-level image
content. Through this experimentation, it is
shown that the proposed scheme can be
efficiently and effectively applied for
medical image retrieval from large
databases, providing unsupervised semantic
interpretation of the results, which can be
further extended by knowledge
representation methodologies. In spite of
these limitations, there are practical
approaches, as shown further on, to
overcome these problems. This paper gives:
1. An overview of the UWB and GPS
sensors as positioning technologies;
2. The mathematical formulation of
Particle Filters and its use for sensor
combination;
3. Some simulated results of the
combination of UWB and GPS
readings to estimate the pose of
vehicles within mixed scenarios
UWB AND GPS SENSORS OVERVIEW
Ultra-Wide Band (UWB) is a quite new
technology with major advantages for
wireless communications. It is based on the
transmission of short pulses in the band
between 3.6 and 10.1GHz. Apart from
communication, it can also be exploited for
positioning, since the distance between two
antennas can be accurately derived through
TOF (time-of-flight). From the localization
point of view, the main advantages of this
system are:
-UWB signals are not affected by multipath
fading.
-The signals can penetrate through objects.
-It exhibits precision ranging at centimeter
level.
-As the signals are of very-low power, there
can be small transmitters and receivers.
On the other hand, GPS is a satellite
geolocalization technique that has been
widely exploited in the last years. Basically,
it uses the signals received from satellites to
develop a tri-lateration process. For
positioning, the system uses two radio
channels in the microwave band, centered at
1575.42MHz and 1227.60MHz. The
accuracy of GPS can be improved by the
usage of differential GPS (DGPS) to achieve
a resolution of tens of centimeters. The
transmitted signals cannot penetrate most
materials, which limits the performance of
the system and makes GPS appropriated
only for outdoor applications, but not for
localization among buildings, dense urban
environments, forests, etc.
Another difference is the type of
information provided by these sensors:
UWB radio devices provide range

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measurements, while the GPS system gives
the position and orientation (x,y,phi) of the
vehicle. For the simulations, Gaussian
models have been adopted for both sensors,
being the uncertainty of the UWB
characterized by the standard deviation of its
measurements and the one of GPS by a 3x3
covariance matrix of the (x,y,phi)
coordinates. Next, the approach for
combining both types of sensor data through
particle filters is presented.
PARTICLE FILTERS FOR SENSOR
COMBINATION IN VEHICLE
POSITIONING
-The basis of the Particle Filters: Bayes
filtering.
-Particular implementation of a Particle
Filter Localization algorithm which
copes with the combination of different
sensory devices.
Bayes filtering
Bayes filters estimate a posterior probability
density, called the belief, denoted Bel(xt)
(belief of being at position x at a time t),
over a space of possible positions
conditioned on the observation data. These
filters are based on the Markov assumption,
for which the past and future data are
independent. Thus, the belief function will
be recursively calculated as:
(1)
where
is a normalization
constant, o
t
is the sensor observation taken
at time t, and a
t
the action executed at time t.
Jointly with an initial probability
distribution, this equation allows us to
estimate future believes about the vehicle
position.For the calculation of Bel(x) two
probability densities must be known
The former is the observation model or
sensor model, and provides the particular
characteristics of each sensor; the later is the
motion model and reflects the motion
behavior of the vehicle.
Particle filters
Particle Filters become an efficient way of
solving the Bayes Filter (1) by representing
the belief function Bel(x) by a set of
weighted samples, or particles, distributed
according to:

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Particles (x
(i)
) represent the plausible
positions of the vehicle following its motion
model. Weights w
(i)
also called importance
factors, represent the “goodness” of each
particle for approaching the real belief
function. This set of pairs particle-weight
permits us to easily integrate information
from different sensors. The position
represented by the weighted mean of the
particles will be assumed as the vehicle
location. The Sequential Importance
Sampling (SIS) Algorithm is followed for
implementing the particle filter. It is divided
in four stages
Step 1: Prediction.
Draw the set of m particles according to the
last motion action.
Step 2: Update.
Assuming the sensors are mutually
independent, the weights for particles are
updated as:
where N is the number of different
observations. Particularizing to our case, the
available observations will be range
measurements provided by UWB sensors,
positions supplied by GPS, or both, and thus
their respective sensor models are
considered.
Step 3: Normalization.
The new weights are normalized to represent
a probability distribution as:
Step 4: Resampling.
This stage aims to avoid particle
impoverishment. In our approach,
resampling is implemented as a systematic
method, which is executed when the number
of high-weighted particles is under a given
threshold. The evolution of the filter
maintains a set of particles that accurately
represent the vehicle pose. . Christo Ananth
et al. [21] discussed about E-plane and H-
plane waveguides (Microwave Engineering)
applicable to image processing. Christo

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Ananth et al. [22] discussed about principles
of electronic devices to explain this
application.
UWB-GPS combined results
We have setup the simulated indoor +
outdoor environment depicted in Fig using
200 particles and 4 UWB beacons inside
each warehouse. In this scenario, as the
vehicle goes out the first warehouse, it loses
UWB signals but starts to receive GPS
readings. At this transition area, although the
vehicle eventually only receives readings
from 2 or less UWB beacons, the
localization error reduced due to the
measures provided by the GPS. Christo
Ananth et al. [23] gave a brief outline on
Electronic devices and circuits which is the
basis for formation of patterns.
Fig.Vehicle localization within a combined
indoor outdoor environment. Marks on the
path indicate the estimated positions of the
vehicle. Note than when both sources of
information are jointly available (at
transition areas), the inaccuracy of the GPS
is corrected, permitting the vehicle to pass
through the gates.
Fig.Localization error of the vehicle with
respect to the ground truth path for the
mixed scenario. Note the accuracy in the
pose estimation along indoor as well as in
mixed areas where both UWB and GPS
observations are combined.
CONCLUSION
This paper describes a probabilistic
framework for the positioning of a vehicle in
a combined indoor + outdoor scenario. The
performance of UWB sensor technology for
indoor positioning and GPS for outdoor
areas is studied. Simulated experiments have
demonstrated the suitability of the approach
.For active tracking and positioning
applications, the short-pulse UWB
techniques offer distinct advantages. The
same approach can be exploited for
extended-operation RF identification
(RFID), for monitoring a VIP on grounds of
security or even an accused under
imprisonment during transfer from one place

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to another, in mobile robots and to check
smuggling of goods.
References:
[1] Christo Ananth, I.Uma Sankari, A.Vidhya, M.Vickneshwari,
P.Karthiga, “Efficient Sensor Network for Vehicle Security”,
International Journal of Advanced Scientific and Technical
Research (IJASR), Volume 2, Issue 4, March-April 2014,pp – 871-
877
[2] Christo Ananth, C.Sudalai@UtchiMahali, N.Ebenesar
Jebadurai, S.Sankari@Saranya, T.Archana, “Intelligent sensor
Network for Vehicle Maintenance system”, International Journal
of Emerging Trends in Engineering and Development (IJETED),
Vol.3, Issue 4, May 2014, pp-361-369
[3] Christo Ananth, S.Shafiqa Shalaysha, M.Vaishnavi, J.Sasi
Rabiyathul Sabena, A.P.L.Sangeetha, M.Santhi, “Realtime
Monitoring Of Cardiac Patients At Distance Using Tarang
Communication”, International Journal of Innovative Research in
Engineering & Science (IJIRES), Volume 9, Issue 3,September
2014,pp-15-20
[4] Christo Ananth, G.Poncelina, M.Poolammal, S.Priyanka,
M.Rakshana, Praghash.K., “GSM Based AMR”, International
Journal of Advanced Research in Biology, Ecology, Science and
Technology (IJARBEST), Volume 1,Issue 4,July 2015, pp:26-28
[5] Christo Ananth, Kanthimathi, Krishnammal, Jeyabala, Jothi
Monika, Muthu Veni, “GSM Based Automatic Electricity Billing
System”, International Journal Of Advanced Research Trends In
Engineering And Technology (IJARTET), Volume 2, Issue 7, July
2015), pp:16-21
[6] Christo Ananth, G.Gayathri, M.Majitha Barvin, N.Juki Parsana,
M.Parvin Banu, “Image Segmentation by Multi-shape GC-
OAAM”, American Journal of Sustainable Cities and Society
(AJSCS), Vol. 1, Issue 3, January 2014, pp 274-280
[7] Christo Ananth, D.L.Roshni Bai , K.Renuka, C.Savithra,
A.Vidhya, “Interactive Automatic Hepatic Tumor CT Image
Segmentation”, International Journal of Emerging Research in
Management &Technology (IJERMT), Volume-3, Issue-1, January
2014,pp 16-20
[8]Christo Ananth, D.L.Roshni Bai, K.Renuka, A.Vidhya,
C.Savithra, “Liver and Hepatic Tumor Segmentation in 3D CT
Images”, International Journal of Advanced Research in Computer
Engineering & Technology (IJARCET), Volume 3,Issue-2,
February 2014,pp 496-503
[9] Christo Ananth, A.Sujitha Nandhini, A.Subha Shree,
S.V.Ramyaa, J.Princess, “Fobe Algorithm for Video Processing”,
International Journal of Advanced Research in Electrical,
Electronics and Instrumentation Engineering (IJAREEIE), Vol. 3,
Issue 3,March 2014 , pp 7569-7574
[10] Christo Ananth, Karthika.S, Shivangi Singh, Jennifer
Christa.J, Gracelyn Ida.I, “Graph Cutting Tumor Images”,
International Journal of Advanced Research in Computer Science
and Software Engineering (IJARCSSE), Volume 4, Issue 3, March
2014,pp 309-314
[11] Christo Ananth, G.Gayathri, I.Uma Sankari, A.Vidhya,
P.Karthiga, “Automatic Image Segmentation method based on
ALG”, International Journal of Innovative Research in Computer
and Communication Engineering (IJIRCCE), Vol. 2, Issue 4, April
2014,pp- 3716-3721
[12] Christo Ananth, A.S.Senthilkani, S.Kamala Gomathy,
J.Arockia Renilda, G.Blesslin Jebitha, Sankari @Saranya.S.,
“Color Image Segmentation using IMOWT with 2D Histogram
Grouping”, International Journal of Computer Science and Mobile
Computing (IJCSMC), Vol. 3, Issue. 5, May 2014, pp-1 – 7
[13] Christo Ananth, A.S.Senthilkani, Praghash.K, Chakka
Raja.M., Jerrin John, I.Annadurai, “Overlap Wavelet Transform
for Image Segmentation”, International Journal of Electronics
Communication and Computer Technology (IJECCT), Volume 4,
Issue 3 (May 2014), pp-656-658
[14] Christo Ananth, S.Santhana Priya, S.Manisha, T.Ezhil Jothi,
M.S.Ramasubhaeswari, “CLG for Automatic Image
Segmentation”, International Journal of Electrical and Electronics
Research (IJEER), Vol. 2, Issue 3, Month: July - September 2014,
pp: 51-57
[15] Christo Ananth, R.Nikitha, C.K.Sankavi, H.Mehnaz,
N.Rajalakshmi, “High Resolution Image Reconstruction with
Smart Camera Network”, International Journal of Advanced
Research in Biology, Ecology, Science and Technology
(IJARBEST), Volume 1,Issue 4,July 2015, pp:1-5
[16] Christo Ananth, B.Prem Kumar, M.Sai Suman, D.Paul
Samuel, V.Pillai Vishal Vadivel, Praghash.K., “Autonomous
Mobile Robot Navigation System”, International Journal of
Advanced Research in Biology, Ecology, Science and Technology
(IJARBEST), Volume 1,Issue 4,July 2015,pp:15-19
[17] Christo Ananth , Mersi Jesintha.R., Jeba Roslin.R., Sahaya
Nithya.S., Niveda V.C.Mani, Praghash.K., “Vision based Path
Planning and Tracking control using Mobile Robot”, International
Journal of Advanced Research in Biology, Ecology, Science and
Technology (IJARBEST), Volume 1,Issue 4,July 2015, pp:20-25
[18] Christo Ananth, S.Suryakala, I.V.Sushmitha Dani, I.Shibiya
Sherlin, S.Sheba Monic, A.Sushma Thavakumari, “Vector Image
Model to Object Boundary Detection in Noisy Images”,
International Journal of Advanced Research in Management,

International Conference on Recent Advances in Management, Architecture, Technology and Engineering
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Organized by
International Journal of Advanced Research in Management, Architecture, Technology and Engineering
(IJARMATE)
21
st
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Architecture, Technology and Engineering (IJARMATE), Volume
1,Issue 2,September 2015, pp:13-15
[19] Christo Ananth,” Geo-cutting Liver Tumor”, International
Journal of Advanced Research in Management, Architecture,
Technology and Engineering (IJARMATE), Volume 2,Issue 3,
March 2016,pp:122-128
[20] Christo Ananth, K.Kalaiselvi, C.Kavya, S.Selvakani,
P.Sorimuthu Iyan, “Patterns for Next generation Database Systems
- A study”, International Journal of Advanced Research in
Management, Architecture, Technology and Engineering
(IJARMATE), Volume 2, Issue 4, April 2016, pp: 114-119
[21] Christo Ananth, S.Esakki Rajavel, S.Allwin Devaraj,
M.Suresh Chinnathampy. "RF and Microwave Engineering
(Microwave Engineering)." (2014): 300,ACES Publishers
[22] Christo Ananth, S.Esakki Rajavel, S.Allwin Devaraj,
P.Kannan. "Electronic Devices." (2014): 300, ACES Publishers.
[23] Christo Ananth,W.Stalin Jacob,P.Jenifer Darling Rosita. "A
Brief Outline On ELECTRONIC DEVICES & CIRCUITS."
(2016): 300.
[24] Leonard G. C. Hamey, Colin Priest, “Automatic Number Plate
Recognition for Australian Conditions”, Proceedings of the Digital
Imaging Computing: Techniques and Applications (DICTA), pp.
14- 21, December 2005.
[25] Yo-Ping Huang, Shi-Yong Lai,Wei-Po Chuang, “A Template-
ased Model for License Plate Recognition”, IEEE International
Conference on Networking, Sensing & Control,March 21-23, 2004