BORDER SECURITY USING WINS

A technical seminar submitted in partial fulfilment of the requirement for the award of degree

BACHELOR OF TECHNOLOGY

In

ELECTRONICS & COMMUNICATION ENGINEERING

By

SANTHOSH PATLOLLA (11211A04D0)

Under the esteemed guidance of

T.P.Kausalya Nandan M.Tech, LMISTE, MIEEE Assistant Professor,

Department of Electronics and Communication Engineering

B.V.RAJU INSTITUTE OF TECHNOLOGY

UGC-AUTONOMOUS

(Approved by AICTE, Accredited by NBA and NAAC) (Affiliated to JNTU, Hyderabad)

Vishnupur, Narsapur, Medak DIST 502313 2014-2015

CERTIFICATE This is to certify that the Projecttechnical seminar work entitled BORDER SECURITY USING WINS is being submitted by Mr.SPATLOLLA SANTHOSH in partial fulfillment of the requirement for the award of the degree of B.Tech. in Electronics & Communication Engineering, by Jawaharlal Nehru Technological University Hyderabad is a record of bonafide work carried out by him under my guidance..

GUIDE Dr.I.A.Pasha T.P.Kausalya Nandan M.Tech, LMISTE, MIEEE HOD .Dept of ECE Assistant Professor

EXTERNAL EXAMINER

ABSTRACT

Wireless Integrated Network Sensors (WINS) now provide a new monitoring and control capability for transportation, manufacturing, health care environmental monitoring, and safety and security. WINS combine sensing, signal processing, decision capability, and wireless networking capability in a compact, low power system. WINS systems combine micro sensor technology with low power sensor interface, signal processing, and RF communication circuits. The need for low cost presents engineering challenges for implementation of these systems in conventional digital CMOS technology. This paper describes micro-power data converter, digital signal processing systems, and weak inversion CMOS RF circuits. The digital signal processing system relies on a continuously operating spectrum analyzer. Finally, the weak inversion CMOS RF systems are designed to exploit the properties of high-Q inductors to enable low power operation. This paper reviews system architecture and low power circuits for WINS.

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ACKNOWLEDGEMENT

Firstly, I would like to acknowledge T.P.Kausalya Nandan (Technical Seminar Coordinator) for guiding us on how to go on with technical seminar writing. Without his guidance our seminar report would not be in this state. Moreover, my sincere thanks goes to my seminar guide Mr T.P.Kausalya Nandan for guiding and giving timely feedback while writing my draft seminar report and he has also tipped me on what should include in good seminar writing and this idea helped me a lot while writing whole of my draft seminar report . I would also like to thanks college ICT section for providing internet access for 24*7 which has helped in finding sources for writing my seminar report.

iiTABLE OF CONTENTS

BORDER SECURITY USING 1

Abstract i

ACKNOWLEDGEMENt ii

Table of Contents iii

List of Figures iv

List of Abbreviations v

1INTRODUCTION 1

2 EXISTING BORDER PATROL TECHNIQUES 2

3 WINS SYSTEM ARCHITECTURE AND BORDER SENSE 3

4 WINS NODE ARCHITECTURE 4

Block Diagram of WINS 6

5 ROUTING BETWEEN NODES AND SHORTEST DISTANCE ALGORITHM 7

WINS MICRO SENSORS AND WINS MICRO SENSOR INTERFACE CIRCUITS 8

7 REMOTE BATTLE FIELD SENSOR SYSTEM (REMBASS): 11

8 WINS DIGITAL SIGNAL PROCESSING AND PSD COMPARISION 14

9 WINS CHARACTERISTICS & APPLICATIONS 15

10 DESIGN CONSIDERATION 16

11Conclusion 17

References 18

iiiLIST OF FIGURES

Figure 1 -Distributed sensors at Border 2

Figure 2 -The wireless integrated network sensor (WINS) architecture 3

Figure 3 (a) Node Connections. (b) WINS nodes (shown as disks). 5

Figure 4 shows the block diagram of the wireless integrated network sensor (WINS) . This

block diagram shows the working principle of the WINS. 6

Figure 5 -Nodal distance and Traffic 7

Figure 6 -Routing Matrix 7

Figure 7 (a) A micrograph of the thermopile junction array in 9

Figure 8 -WINS -ADC A block diagram of the pulse code modulator part of the -ADC

showing the location of the input analog modulator and output digital demodulator chopping

blocks. 10

Figure 9 - REMBASS. 11

Figure 10 -WINS micro power spectrum analyzer architecture. 14

Figure 11- Comparator plot 15

Figure 12- Enclosure 16

ivLIST OF ABBREVIATIONS

Sl. No.

Terms

Descriptions

1

WINS

Wireless integrated network sensors2

REMBASS

Remote battle field sensor system3

UGS

Unattended Ground Sensors4

RSTA

Reconnaissance, surveillance, and target acquisition5

IR

Passive infrared sensor6

MAG

Magnetic sensor7

SA

Seismic/acoustic sensor8

SMS

Sensor Monitoring Set9

PMS

Portable monitoring set10

SSS

Sensor Signal Simulator11

FLOT

Forward line of own troops

v1 INTRODUCTION

Wireless Integrated Network Sensors (WINS) provide distributed network and Internet access to sensors, controls, and processors that are deeply embedded in equipment, facilities, and the environment. The WINS network is a new monitoring and control capability for applications in transportation, manufacturing, health care, environmental monitoring, and safety and security. WINS combine micro-sensor technology, low power signal processing, low power computation, and low power, low cost wireless networking capability in a compact system. Recent advances in integrated circuit technology have enabled construction of far more capable sensors, radios, and processors at low cost, allowing mass production of sophisticated systems that link the physical world to networks. Scales will range from local to global, with applications including medicine, security, factory automation, environmental monitoring, and condition-based maintenance. Compact geometry and low cost allows WINS to be embedded and distributed at a small fraction of the cost of conventional wire line sensor and actuator systems. Future applications of distributed embedded processors and sensors will require massive numbers of devices. In this paper we have concentrated in the most important application, Border Security.

WINS Initiated in 1993 under Defence advance research project agency (DARPA) in US. LWIM (Low power wireless integrated micro sensor) program began in 1995 for further development of WINS sponsored by DARPA. In 1998, WINS NG introduced for wide variety of application. The LWIM project for multi hop, self-assembled, wireless network algorithms for operating at micro power levels.

12 EXISTING BORDER PATROL TECHNIQUES

Border patrol has extensively been based on human involvement. However, the relative cost for the increasing number of personnel as well as the diminishing accuracy through human-only surveillance has required the involvement of high-tech devices in border patrol. Among these, Unmanned Aerial Vehicles (UAVs) for aerial surveillance have recently been used to automatically detect and track illegal border crossing. Due to the large coverage and high mobility of the UAVs, the intensive human involvement in low-level surveillance activities can be reduced. However, similar to the Conventional border patrol systems, UAVs alone cannot cover the whole border at any time. Moreover, the UAVs have significantly higher costs and accident rates than those of manned aircrafts and require large human footprint to control their activities. In addition, inclement weather conditions can also impinge on the surveillancecapability of UAVs.[1]

Compared with the existing border patrol techniques, Border Sense provides the following advantages: (1) the multimedia sensors provide accurate detection as well as large detection range; (2) the ground sensors provide additional information that cannot be detected by the multimedia sensors, e.g. in cases where the intruder is hidden behind an obstacle that cannot be detected by the imaging sensor; (3) the underground sensors guarantee the proper system functionalities where aboveground visible devices are not preferred for concealment purposes;

(4) mobile sensors provide intrusion tracking capability to track the intruders after they have been detected; and (5) by in network processing, the heterogeneous sensors cooperatively detect the intrusion and report the results to a remote administrator. Accordingly, both the deployment and operational cost of the border patrol system can significantly be decreased.

Figure 1 -Distributed sensors at Border

23 WINS SYSTEM ARCHITECTURE AND BORDER SENSE

In contrast to conventional wireless networks, the WINS network must support large numbers of sensors in a local area with short range and low average bit rate communication (less than 1 - 100 kbps). The network design must consider the requirement to service dense sensor distributions with an emphasis on recovering environment information. We exploit the small separation between WINS nodes to provide multi hop communication, with the power advantages outlined earlier. Since for short hops the transceiver power consumption for reception is nearly equal to that of transmission, the protocol should be designed so that radios are off as much of the time as possible. That is, the MAC should include some variant of TDMA. This requires that the radios periodically exchange short messages to maintain local synchronism. The abundant bandwidth that results from the spatial re-use of frequencies and local processing ensures that relatively few conflicts will result in these requests, and so simple mechanisms can be used. A low-power protocol suite that embodies these principles has been developed, including boot-up, MAC, energy-aware routing, and interaction with mobile units. It indicates the feasibility of achieving distributed low-power operation in a flat multi-hop network.

The multi hop communication has been shown in the figure 2. The figure represents the general structure of the wireless integrated network sensors (WINS) arrangement. small wins [2]

Figure 2 -The wireless integrated network sensor (WINS) architecture

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4 WINS NODE ARCHITECTURE

The WINS node architecture (Figure 3) is developed to enable continuous sensing, event detection, and event identification at low power. Since the event detection process must occur continuously, the sensor, data converter, data buffer, and spectrum analyser must all operate at micro power levels. In the event that an event is detected, the spectrum analyser output may trigger the microcontroller. The microcontroller may then issue commands for additional signal processing operations for identification of the event signal. Protocols for node operation then determine whether a remote user or neighbouring WINS node should be alerted. The WINS node then supplies an attribute of the identified event, for example, the address of the event in an event look-up-table stored in all network nodes. Total average system supply currents must

able, and efficient network operation is obtained with intelligent sensor nodes that include sensor signal processing, control, and a wireless network interface. Distributed network sensor devices must continuously monitor multiple sensor systems, process sensor signals, and adapt to changing environments and user requirements, while completing decisions on measured signals.

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Figure 3 (a) Node Connections. (b) WINS nodes (shown as disks).

The above figure shows the node connections deployed in WINS. By the fig it can be seen that several nodes are connected together and also with the Gateway which is used for Conventional Communication, Internet Connectivity and Remote Maintenance and Re-configurability. This type of architecture will be low cost, consumes low power, multi hop, multiply redundant and reconfigurable.

For the particular applications of military security, the WINS sensor systems must operate at

low power, sampling at low frequency and with environmental background limited sensitivity.

The micro power interface circuits must sample at dc or low frequency where 1/f noise in

these CMOS interfaces is large.

The micro power signal processing system must be implemented at low power and with limited word length. In particular, WINS applications are generally tolerant to latency. The WINS node event recognition may be delayed by 10 100 msec, or longer. [3]

5Block Diagram of WINS

Figure 4 shows the block diagram of the wireless integrated network sensor (WINS) . This

block diagram shows the working principle of the WINS.

65 ROUTING BETWEEN NODES AND SHORTEST

DISTANCE ALGORITHM

The sensed signals are then routed to the major node. This routing is done based on the shortest distance. That is the distance between the nodes is not considered, but the traffic between the nodes is considered. This has been depicted in the figure 5. In the figure, the distances between the nodes and the traffic between the nodes have been clearly shown. For example, if we want to route the signal from the node 2 to node 4, the shortest distance route will be from node 2 via node 3 to node 4. But the traffic through this path is higher than the path node 2 to node 4. Whereas this path is longer in distance.

Figure 5 -Nodal distance and Traffic

Figure 6 -Routing Matrix

In this process we find mean packet delay, if the capacity and average flow are known. From the mean delays on all the lines, we calculate a flow-weighted average to get mean packet delay for the whole subnet. The weights on the arcs in the figure 5 give capacities in each direction measured in kbps.

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In figure 6 the routes and the number of packets/sec sent from source to destination are shown. For example, the E-B traffic gives 2 packets/sec to the EF line and also 2 packets/sec to the FB line. The mean delay in each line is calculated using the formula

Ti =1/(c-

Ti = Time delay in sec

C= Capacity of the path in Bps

= Mean flow in packets/sec.

WINS MICRO SENSORS AND WINS MICRO SENSOR INTERFACE CIRCUITS

Many important WINS applications require the detection of signal sources in the presence of environmental noise. Source signals (seismic, infrared, acoustic, and others) all decay in amplitude rapidly with radial distance from the source. To maximize detection range, sensor sensitivity must be optimized. In addition, due to the fundamental limits of background noise, a maximum detection range exists for any sensor. Thus, it is critical to obtain the greatest sensitivity and to develop compact sensors that may be widely distributed. Clearly, micro electromechanical systems (MEMS) technology provides an ideal path for implementation of

these highly distributed systems. WINS sensor integration relies on structures that are flip-chip bonded to a low temperature, co-fired ceramic substrate. This sensor-substrate sensorstrate is

then a platform for support of interface, signal processing, and communication circuits. Examples of WINS micro seismometer and infrared detector devices are shown in Figure 7.8

Figure 7 (a) A micrograph of the thermopile junction array in

(b)This dual pixel device provides object presence and motion sensing. The WINS thermopile operates without the need for a voltage or current bias and provides a noise equivalent power of 1.8 nW/(Hz)1/2 (a sensitivity level limited by thermal noise).

The WINS micro sensor systems must be monitored continuously by the CMOS micro power analog -to-digital converter (ADC). As was noted above, power requirements constrain the ADC design to power levels of 30W or less.

9Implementation of low noise ADC systems in CMOS encounters severe 1/f input noise with input noise corner frequencies exceeding 100 kHz. An IF frequency of 1/8 th of the ADC sampling frequency is chosen. The low thermopile sensor source impedance limits the amplitude of charge injection noise that would result from signal switching. The required demodulation of the IF signal to the desired baseband is accomplished on the digital code

modulated signal, rather than on the analog signals. This both simplifies architecture and avoids additional injected switching noise. The architecture of the chopped - ADC is shown inFigure 8.[3]

Figure 8 -WINS -ADC A block diagram of the pulse code modulator part of the -ADC showing the location of the input analog modulator and output digital demodulator chopping blocks.

107 REMOTEBATTLEFIELDSENSORSYSTEM

(REMBASS):

What is UGS (Unattended Ground Sensors)?

A ground sensor is deployed permanently on the ground in the open. The deployment mode varying from buried, to surface-mounted. An unattended sensor works autonomously, without requiring human attention for its operation

It uses remotely monitored sensors emplaced along likely enemy avenues of approach. REMBASS is a UGS system that detects, classifies, and determines direction of movement of personnel, wheeled vehicles, and tracked vehicles. It provides worldwide deployable, day/night, all-weather, early warning surveillance and target classification. Units operate up to 90 days, or longer, without maintenance.

REMBASS sensors are built for any level of conflict, including special operations, low intensity conflict, and counter narcotics operations. The sensors are placed along likely avenues ofapproach or intrusion and respondto seismic and acoustic disturbances, infraredenergy,and magnetic field changes. Thesensor information is incorporated into short,digital

messages and communicated by VHF radio burst transmission.[4]

Figure 9 - REMBASS.

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The system provides division, brigade, and battalion commanders with information from beyond the forward line of own troops (FLOT), and enhances rear area protection. It can be deployed anywhere in the world in a tactical environment in support of reconnaissance, surveillance, and target acquisition (RSTA) operations. The system consists of eleven major components;

Magnetic Sensor: This is a hand-emplaced, MAG sensor. The MAG sensor detects vehicles (tracked or wheeled) and personnel carrying ferrous metal. The monitor uses two different (MAG and IR) sensors and their identification codes to determine direction of travel.

Seismic Acoustic Sensor: This is a hand-emplaced SA classifying sensor. It detects targets and classifies them as unknown, wheeled vehicle, tracked vehicle, or personnel.

Passive Infrared Sensor: This is a hand-emplaced, IR detecting sensor. The senor detects tracked or wheeled vehicles and personnel. It also provides information on which to base a count of objects passing through its detection zone and reports their direction of travel relative to its location.

Radio Repeater: This is an expendable/recoverable, digital/analog radio repeater used to extend the broadcast range of radio messages from anti-intrusion sensors to a monitoring set. It

Sensor Monitoring Set: The SMS has a dual channel receiver with a permanent hard copy recorder and a temporary visual display (TVD). The SMS receives processes, displays, and records sensor information relating to 60 sensor ID codes. Detections and classification are displayed as: dashes (-) for unknown targets, (T) for tracked vehicles, (W) for wheeled vehicles, and (P) for personnel. The TVD can simultaneously display up to ten sensor ID codes with detection or classification information. A keyboard allows the operator to program the SMS operation: set radio frequency (RF) channels, establish hard copy recorder format, initiate system operational checks or built in test (BIT), and calculate target speed. A separate display shows the keyboard functions and calculations.

Radio Frequency Monitor: This is a single-channel PMS with a TVD. The PMS receives, processes, and displays sensor ID codes and detection/classification messages.

12(7) Code Programmer: The programmer is a portable device used to program sensors and repeaters to the desired operating channel, ID code, mission life, arm mode, and gain. It is also used to condition newly installed batteries in sensors and repeaters. It has a built in visual self-test to ensure the proper information programmed into the sensor or repeater.

Antenna Group: The antenna group consists of an Omni -directional unity gain antenna, a mast assembly, a pre-amplifier suitable for mast mounting and an RF multi- coupler. It is used with the SMS and the PMS. Up to four monitoring devices can use the antenna group simultaneously.

Power Supply: The power supply is a custom fly back-type switching regulator that converts external power sources (24 volts direct current (dc), 115 or 220 volts alternating current) to 12 volts dc nominal prime power. The power supply can be used to power the SMS, repeater or SSS.

Mounting Rack: The mounting rack is an aluminum angle shock mounted rack. It is used to mount the repeaters in helicopters.

Sensor Signal Simulator (SSS): The SSS is similar in appearance to the SMS. It has the capability to receive, record, edit, copy, and retransmit an operational scenario involving any two of the 599 REMBASS channels. It also has the capability to transmit pre-recorded scenarios. [4]

138 WINS DIGITAL SIGNAL PROCESSING AND PSD

COMPARISION

If a stranger enters the border, his foot-steps will generate harmonic signals. It can be detected as a characteristic feature in a signal power spectrum. Thus, a spectrum analyser must be implemented in the WINS digital signal processing system. The spectrum analyser resolves theWINS input data into a low-resolution power spectrum. Power spectral density (PSD) in each frequency bins is computed with adjustable band location and width. Bandwidth and position

for each power spectrum bin is matched to the specific detection problem. The WINS spectrum

and wireless network interface components, achieves low power operation by maintaining only the micropower components in continuous operation. The WINS spectrum analyzer system, shown in Figure 10 contains a set of parallel filters.

Figure 10 -WINS micro power spectrum analyzer architecture.

Each filter is assigned a coefficient set for PSD computation. Finally, PSD values are compared with background reference values In the event that the measured PSD spectrum values exceed that of the background reference values, the operation of a microcontroller is triggered The micro controller sends a HIGH signal, if the difference is high. It sends a LOW signal, if the difference is low. For a reference value of 25db, the comparison of the DFT signals is shown in the figure 11. [4]

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Figure 11- Comparator plot

9 WINS CHARACTERISTICS & APPLICATIONS

Characteristics:

Support large numbers of sensor.

Dense sensor distributions.

These sensor are also developed to support short distance RF communication

Internet access to sensors, controls and processor

Applications:

On a global scale, WINS will permit monitoring of land, water, and air resources for environmental monitoring.

On a national scale, transportation systems, and borders will be monitored for efficiency, safety, and security.

On a local, enterprise scale, WINS will create a manufacturing information service for cost and quality control. [5]

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10 DESIGN CONSIDERATION

Reliability: The system must be reliable so that the probability of failures and faulty operations must be very less.

Energy: There are four way in which node consumes energy.

Sensing: Choosing right sensor for the job can improve the system performance and to consume less power.

Computation: The sensor must be chosen so that the speed of computation can be very fast and less faults.

Storing: The sensor must have sufficient storage to store the sensed data so that it can be communicated.

Communicating: The communicating between sensors is very important factor when it is used for border security. There must not be any faults during communicating the sensed data between various nodes and the gateway.

The sensor must be design to minimize the likelihood of environment effect of wind, rain, snow etc. The enclosure is manufacture from clear acrylic material. Otherwise the sensor

may damage due to weather effects and may give fault results.[6]

Figure 12- Enclosure

1611 Conclusion

A series of interface, signal processing, and communication systems have been implemented in micro-power CMOS circuits. A micro-power spectrum analyzer has been developed to enable low power operation of the entire WINS system. Thus WINS require a Microwatt of power. But it is very cheaper when compared to other security systems such as RADAR under use. It is even used for short distance communication less than 1 Km. it produces a less amount of delay. Hence it is reasonably faster. On a global scale, WINS will permit monitoring of land, water, and air resources for environmental monitoring. On a national scale, transportation systems, and borders will be monitored for efficiency, safety, and security.

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REFERENCES

Z. Sun, P. Wang, M. . C. .Vuran, M. A. Al-Rodhaan, A. M. Al-Dhelaan and I. . F. Akyildiz,

border sense:border patrol through advanced wireless sensor network, Adhoc network(Elsevier), vol. 9, pp. 468-477, 2011.

G. J. Pottie and W. J Kaiser, Wireless Integrated Network Sensors (WINS):, Principles and Practice, p. 10, 21 sept 2013.

G. Asada, M. Dong, T. Lin, F. Newberg and ,. Pottie, Wireless Integrated Network

Sensors: Low Power Systems on a Chip, Rockwell Science Center, vol. 2, pp. 17-21, 1997.

Z. HAIG, Networked unattended ground sensors for battlefield, AARMS, vol. 3, no. 3, p. 387399, 2004.

S. Natkunanathan and J. Pham , IRELESS INTEGRATED NETWORKED SENSORS:,

56-125B Engineering, vol. 4, pp. 12-14, 1996.

W. Fang, An Adaptive Transmission Scheme for Wireless Sensor Networks,

International Journal of Future Generation Communication and Networking, vol. 6, no. no.1, pp. 45-48, 2013.

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