Guided by M.MARY SUSANNA,HOD/ ECE DEPT … UNIVERSITY Guided by M.MARY SUSANNA,HOD/ ECE DEPT ... gait such as running, ... unfavorable light conditions can result in completely

MULTI SENSOR FOR RELIABLE SOLDIER AND INDOOR NAVIGATION SYSTEM

A.GANESH ([email protected]) M.TECH, K.GANESHKUMAR M.TECH ([email protected])

PRIST UNIVERSITY

Guided by M.MARY SUSANNA,HOD/ ECE DEPT PRIST UNIVERSITY,KUMBAKONAM,TAMILNADU

ABSTRACT

This paper represents a first step in developing an

indoor navigation system based only on Micro-

Electro-Mechanical Systems (MEMS) accelerometer

and gyroscope sensors. The major advantage of the

proposed inertial navigation system consists on the

fact that it does not require any complex

infrastructure to be able to operate. For determining

the distance it uses three axis accelerometer sensors,

while the direction of the user is determined from the

gyroscope angular rate data. As no infrastructure is

used, the cost of such a system is low.

I. INTRODUCTION

In our days, pedestrian navigation represents a

challenging application for navigation technologies.[1,3]

A pedestrian navigation system must work in urban areas,

and also indoors, where the coverage of GNSS and most

of the radio navigation systems is poor.[5]

The basic principle on which these systems

operate is quite simple and it consists in three phases,

namely: step detection, step length estimation and

Navigation-solution update . For determining the

steps the algorithm uses a body mounted accelerometer

sensor.[1] The exact moment when a step occurs can be

determined from the zero crossings or from the peaks in

the accelerometer signals. In our approach we used the

signal peaks for determining the number of steps. [1]

The second phase of the algorithm consists in estimating

the length of each step. This can be correlated with the

variance of the accelerometer measurements, slope of the

terrain and vertical velocity. In our case we used a fixed

value for estimating the length of each step.[8]

II. LITERATUE SURVEY a. SURVEY 1:

GPS signals are not always available because they can be

blocked by high buildings, canyons or forests among

others. It can be a great problem in certain situations,

such as military maneuvers or even for emergency

responders. Usually, pedestrians are not in places with a

high visibility of the sky, so the reception of the GPS

signal will not be as good as the system needs. A soldier

can be in hidden places, and a firefighter can be indoors.

Both are places in which a good placement of aerials is

not possible. The combined use of inertial sensors and

GPS will yield a high accuracy in the estimation of the

International Journal of Advancements in Research & Technology, Volume 3, Issue 2, February-2014 ISSN 2278-7763 74

Copyright © 2014 SciResPub. IJOART

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pedestrian’s location even when outdoor and indoor

placements are crossed. This work tries to extend the

studies done in vehicles and robots with inertial sensors

to personal navigation. GPS signal jamming both indoors

and outdoors. The main disadvantage is the increasing

error of the system over time and a method able to correct

it is required.

b. SURVEY 2 : Simple pedometers focus on counting steps. Based on

this step count and an average step length, a pedometer

unit can estimate distance traveled . Pedometers do not

have the ability to differentiate between different types of

gait such as running, shuffling or side stepping.

Overshoots tend to occur at slower velocities. Pedometers

must be calibrated for the stride length of the user and

they produce large errors when the user moves in any

other way than his or her normal walking pattern.

c. SURVEY 3 :

Another way of implementing absolute position

estimation is computer vision. Images are compared and

matched against a pre-compiled database. Computer

vision has the advantage that the environment does not

need to be modified, but the approach requires potentially

very large databases. Work is also being done on so-

called Simultaneous Location and Mapping (SLAM)

methods, which don’t require a precompiled database.

However, SLAM systems are not as reliable, may accrue

errors over time and distance, and poor visibility and

unfavorable light conditions can result in completely

false position estimation.

III. EXISITING SYSTEMS

A High Precision Reference Data Set for Pedestrian

Navigation using Foot-Mounted Inertial Sensors

In this paper we present a reference data set that we are

making publicly available to the indoor navigation

community. This reference data is intended for the

analysis and verification of algorithms based on foot

mounted inertial sensors. Furthermore, we describe our

data collection methodology that is applicable to the

analysis of a broad range of indoor navigation

approaches. We employ a high precision optical reference

system that is traditionally being used in the film industry

for human motion capturing and in applications such as

analysis of human motion in sports and medical

rehabilitation. The data set provides measurements from a

six degrees of freedom foot mounted inertial MEMS

sensor array, as well as synchronous high resolution data

from the optical tracking system providing ground truth

for location and orientation. We show the use of this

reference data set by comparing the performance of

algorithms for an essential part of pedestrian dead

reckoning systems for positioning, namely identification

of the rest phase during the human gait cycle.

Fig.1 internal navigation with foot mounted sensor



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IV. PROPOSED SYSTEM

This paper has an idea of tracking the soldier and

navigation between soldier to soldier such as knowing

their speed, distance, height as well as health status of

them during the war, which enables the army personnel to

plan the war strategies. Base station gets location of

soldier from zigbee. It is necessary for the base station to

guide the soldier on correct path if he is lost in the

battlefield. The base station can access the current status

of the soldier which is displayed on the PC. And hence

can take immediate action by sending help for the soldier

or sending backup for threat ahead.

V. PRINCIPLE OF OPERATION

� Detect a step, estimate step length, estimate step

direction

� Step detection thresholds varies, e.g. Sneaking

versus running ,Concrete versus sand.

� Step length varies Outdoors vs. indoors, walking

up or down a slope/stairs, fatigue, situation

dependent.

� Step direction Systems assume first responder

moves ”forward” (in direction of IMU

orientation), but realistic movement patterns

include sidestepping, walking backwards,

crawling.

VI. ADVANTAGE OF PROPOSED SYSTEM

� Gyro (three-axis) Measures

� Accelerometer (three-axis)

� Reliable performance metrics for Zigbee pseudo

range estimates in multipath environments

� Lightweight

� Low-cost

� energy-efficient

� inexpensive sensors

VII. SOFTWARE AND HARDWARE

REQUIREMENTS

a. SOFTWARE SECTION

� EMBEEDED ‘C’ PROGAMMING

� VB 6.0 PROGAMMING

� VB ++ PROGAMMING ( MONTIOR

SECTION VIEW)

VIII. HARDWARE SECTION

� MEMS MAGNETOMETER,

� MEMS PRESSURE SENSOR,

� MEMS ACCELEROMETER

� MICRO PHONE

� ADC

� MICROCONTROLLER

� IEEE 802.15.4 RADIO COMMUNICATION

� RELAY, SPEAKER

� DC POWER SUPPLY 3.3 V, 5V

IX. IMPLEMENTATION OF LOCALIZATION SYSTEM we implemented it in Ubiquitous Device, which is a

sensor network system that performs communication

based on the ZigBee standard. Ubiquitous Device is

equipped with four push switches, one LEDs, and a

general-purpose analog I/O port. MEMS sensor can be

connected to this analog I/O port. Moreover, the collected

data can be sent to a PC by serial communication if the

optional USB port is installed.



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The CPU of this device is PIC16F628A microcontroller

from Microchip Corporation,This MCU operates with a

16 MHz clock speed. It has 32 KB flash memory, 2 KB

SRAM, 1KB EEPROM and can operate on a range of

2V-4V. To enable this device to be programmed C

language. radio controller from Chipcon Inc., which is

used to perform communication based on the ZigBee

standard.

X. MEMS

MEMS inertial measurement units (IMUs) generally

consist of three orthogonal gyroscopes and three

orthogonal accelerometers. By integrating linear

accelerations and rotational velocities provided by the

IMU, a navigation system is capable of tracking the

position, velocity, and attitude of a moving object.

However, due to the integration drift, the position and the

attitude must be periodically corrected. In our Micro-

IMU we apply modern accelerometers and gyroscopes

which feature three-axis technology and integrated

analog-to-digital conversion with automatic temperature

compensation in a one-chip design.

XI. MICROCONTROLLER

I have chosen to use the PIC16F628A

microcontroller from Microchip Corporation. This MCU

operates with a 16 MHz clock speed. It has 32 KB flash

memory, 2 KB SRAM, 1KB EEPROM and can operate

on a range of 2V-4V. It has 14 digital input/output pins

(of which 6 can be used as PWM outputs), 6 analog

inputs, six sleep modes, master/slave SPI serial interface,

and other features that are not very important for the

purpose of this project.

The small physical size (great for a portable device),

adequate memory space, fast clock speed, few

input/output pins (only 16 pins will be used),

compatibility with audio player shield, low-cost, use of

C-programming language, and the fact that I have

previous experience working with it make this

microcontroller an excellent choice for this project.

XII . COMMUNICATION

IEEE 802.15.4 is an IEEE standard that defines

the physical layer and the medium access control (MAC)

layer for a low-speed, low-cost and low-power wireless

personal area network (WPAN). The popular ZigBee

protocol is based on this standard. Each device has a

unique address, and supports both peer-to-peer/mesh

communication and a more structured, star topology.

XIII. SPEAKER

The speaker is used in this project for guiding the

visually impaired persons to navigate independently by

amplifying the pre-defined voice signals.

XIV. IMPLEMENTATION METHODS OF ZIGBEE NETWORKS:

Implementation of a real-time location system

using ZigBee requires setting up a ZigBee coordinator

and then connecting and recording the positions of a

mesh network of static ZigBee routers and end devices.

ZigBee router programmed with tracking software will

then connect to the wireless ZigBee network and send

transmissions every few seconds. An algorithm will

determine the position based upon RF variability.

XV. MONITORING SECTION In this section the processed details are received

through the ZigBee module and are given to PC for

further analysis. The controller an give voice commands

to any soldier working through the Zigbee module and

voice kit.

XVI. STEP-LENGTH-UPDATE

To improve the inertial long term stability, a Step

Length Update (SLU) is included in the navigation filter.

This filter support uses step identification based on

accelerometer data of the IMU, observing the event of a

step and estimating the user step length. The combination



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of step length and the latest heading angle is a dead

reckoning path and is used in the navigation filter in the

UWB/INS integration.

XVII. MOVEMENT MODEL

Identify the steps and step size to obtain the

walking distance

Equation ----------------- (1)

In our paper, we use a simple zero-crossing

algorithm to detect the number of steps. We know that

the vertical acceleration signal crosses the zero line twice

every step.

Hence, we can count the number of zero crossing

points and divide it by two, deriving the number of

walked steps Num_Steps. The step size is calculated by

an empirical equation proposed by engineers from

Analog Device , as shown in Equation (2).

Equation ----------------- (2)

Where Amax and Amin are the maximum and

minimum acceleration in one step, respectively; C is a

constant value, which can be obtained from walking

training. Some more accurate, but also more complex

models for calculating the number of step and step size

can be found in the literature.

XVIII. WORKING OPERATION

This project uses all the above mentioned parts.

The Zigbee receiver continuously receives the latitude

and longitude values for every position of the system and

it is interfaced with the Microcontroller to display the

values in the PC display. The Microcontroller is

programmed to interface the MEMS sensor to distinguish

the distance between the MEMS transceiver and the

obstacle to maintain at 10inch and above. The received

analog signal in the MEMS receiver is converted into the

digital signal using the signal conditioner unit and it is

given to the microcontroller.

The sensor provides an step pulse proportional to

distance. If the width of the pulse is measured in µs then

dividing by 58 will give you the distance in cm, or

dividing by 148 will give the distance in inches.

µs /58=cm or µs /148=inches.

This voice is stored in the microcontroller as the

address values, each address values is used for

recognizing the destinations. The keypad with 4 keys are

used for setting the destination values by analyzing the

latitude and longitude values received in the Liquid

crystal display.

The Zigbee transceiver is connected to the

system and it continuously transmits the values of latitude

and longitude that has been updated using the Zigbee

receiver. The Microcontroller is responsible for

transmitting the digital data through this transceiver and

it is received in another transceiver connected to the PC.

The digital value received in the zigbee transceiver

connected to the PC has the positive and negative values .

The USB port is used to interface the zigbee transceiver

and the PC. Thus the values are continuously transmitted

between the transceiver and the PC.

Fig 2. Pedstrain Tracking using Inertial Sensor



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Fig 3. 3-D output values for Sniper.

Fig 4. Graphical waveform outputs for Snipers.

CONCLUSION

The aim of this work has been the research and

development of a system that will enable personal

navigation in areas where the GPS signal is compromised

and, at the same time, will allow indoor navigation. The

system is designed to cover three points:

• Ability to obtain a better estimate of a pedestrian’s

position in real time.

• 3D location of the user in a building (being able to

discern the floor where the user is located in a

building with several floors).

• To achieve a continuous transition between

outdoor and indoor areas.



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REFERENCES J. Rantakokko et al., “User Requirements for Localization and Tracking Technology: A Survey of Mission-specific Needs and Constraints,” Proc. Int’l. Conf. Indoor Position-ing and Navigation, Zurich, Switzerland, Sept. 2010

2. E.Jacobson et al., “SUO/SAS Geolocation: Land Navigation Using Multiple Integrated Sensors,” Proc. 57th ION Annual Tech. Mtg., Albuquerque, NM, June 2001. 3. D.Landis et al., “A Deep Integration Estimator for Urban Ground Navigation,” Proc. PLANS 2006, San Diego, CA, Apr. 2006.

4. S. Rounds, “Advanced 3-D Locator Indoor Positioningfor Firefighters and

Other First Responders,” WPI PPL Technology Wksp., Worcester, MA, 2008. 5. G. A. Vecchione et al., “DINGPOS, A GNSS-based Multi-sensor Demonstrator for Indoor Navigation: Preliminary Results,” Proc. PLANS 2010, Palm Springs, CA, May 2010 6. W.T.Faulkner et al., “GPS-Denied Pedestrian Tracking in Indoor Environments Using an IMU and Magnetic Compass,” Proc. ION Int’l. Tech. Mtg., San Diego, CA, Jan. 2010.

7. E.Foxlin and S. Wan, “Improved Pedestrian Navigation Based on Drift-Reduced MEMS IMU Chip,” Proc. ION Int’l. Tech. Mtg., San Diego, CA, Jan. 2010. 8. P. Strömbäck et al., “Foot-mounted Inertial Navigation and Cooperative Sensor Fusion for Indoor Positioning,” Proc. ION Int’l. Tech. Mtg., San Diego, CA, Jan. 2010.

9. I. Skog et al., “Zero-Velocity Detection — An Algorithm Evaluation,” IEEE Trans. Biomed. Eng., vol. 57, no. 11, Nov. 2010, pp. 2657–66.

10. J. Callmer, D. Törnqvist, and F. Gustafsson, “Probabilistic Stand Still Detection Using Foot-mounted IMU,” Proc. 13th Int’l. Conf. Info. Fusion, Edinburgh, UK, 2010.

11. K. Pahlavan et al., “Taking Positioning Indoors — Wi-Fi Localization and GNSS, “ InsideGNSS, May 2010.

12. N. Alsindi, B. Alavi, and K. Pahlavan, “Measurement and Modeling of UWB TOA-based Ranging in Indoor Environments,” IEEE Trans. Vehic. Tech., vol. 58, Mar. 2009, pp. 1046–58.



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Guided by M.MARY SUSANNA,HOD/ ECE DEPT … UNIVERSITY Guided by M.MARY SUSANNA,HOD/ ECE DEPT ... gait such as running, ... unfavorable light conditions can result in completely

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