Electromagnetic Field Location using Mobile Actuator Sensor

Networks

Senior Design Project Final Report

ECE 4850: Design III

April 22, 2008

Ryan Keith

Joshua Daley

Instructor Approval ________________________________________ __________________ Dr. YangQuan Chen Date Electrical and Computer Engineering Department Utah State University

Table of Contents

ABSTRACT ....................................................................................................................... 4

1. INTRODUCTION..................................................................................................... 4 1.1. SUBJECT AND PURPOSE ........................................................................................ 4 1.2. HISTORY .............................................................................................................. 5 1.3. PROBLEM STATEMENT ......................................................................................... 6 1.4. SUMMARY OF DESIGN PROCESS ........................................................................... 6 1.5. SUMMARY OF FINAL RESULTS ............................................................................. 7 1.6. ORGANIZATION AND SUMMARY OF REPORT ........................................................ 8

2. PROBLEM ANALYSIS ........................................................................................... 9 2.1. REVIEW OF PROBLEM ........................................................................................... 9 2.2. DESIGN CONSIDERATIONS.................................................................................. 12 2.3. SUMMARY OF SPECIFICATIONS .......................................................................... 15

3. DESIGN ................................................................................................................... 16 3.1. HARDWARE ........................................................................................................ 16

3.1.1. Motes and Robot Electronics ........................................................................ 18 3.1.2. Sensor ............................................................................................................ 18 3.1.3. Power Conditioning ...................................................................................... 19 3.1.4. Signal Conditioning Circuit .......................................................................... 21 3.1.5. EM Source and Antenna Attenuation ............................................................ 22

3.2. SOFTWARE ......................................................................................................... 24

4. IMPLEMENTATION ............................................................................................ 26 4.1. HARDWARE ........................................................................................................ 26 4.2. SOFTWARE ......................................................................................................... 29

5. TESTING ................................................................................................................. 30 5.1. HARDWARE ........................................................................................................ 30 5.2. SOFTWARE ......................................................................................................... 31

6. FINAL SCOPE OF WORK STATEMENT ......................................................... 32 6.1. WHAT HAS BEEN DONE ...................................................................................... 32 6.2. LESSONS LEARNED ............................................................................................. 32 6.3. FUTURE DESIGN CONSIDERATIONS AND REVISIONS ............................................ 33

7. PROJECT MANAGEMENT ................................................................................. 33 7.1. SCHEDULING ...................................................................................................... 34 7.2. COST .................................................................................................................. 36

8. CONCLUSION ....................................................................................................... 36

List of Figures

Figure 1: Example of an Isotropic Electromagnetic field source in the xy-plane ............ 10 Figure 2: High level flow diagram of sensor and interface .............................................. 17 Figure 3: Receiver Pin out ................................................................................................ 19 Figure 4: Power conditioning circuit ................................................................................ 20 Figure 5: Signal conditioning circuit ................................................................................ 21 Figure 6: EM Source ......................................................................................................... 22 Figure 7: EM source pinout .............................................................................................. 23 Figure 8: System schematic .............................................................................................. 27 Figure 9: System hardware ............................................................................................... 28 Figure 10: Integrated system hardware ............................................................................. 29

Abstract

We, Ryan Keith and Joshua Daley, designed, developed, and tested a system that

locates electromagnetic fields using the MAS-net platform. The MAS-net platform

enables the finding of the electromagnetic field if it is moving. The requirements for this

project include providing cooperative control, sharing and handling information between

motes, locating and tracking algorithms, integrating electromagnetic sensors into MicaZ

motes, and implementing software into the current platform. This report details the

specifics of how this was done and also the successes and failures that occurred in the

duration of the project.

1. INTRODUCTION

1.1. Subject and Purpose

The subject of this report outlines the design process, implementation, and testing

of an electromagnetic field finding system. This system is a proof of concept system that

illustrates one way to solve the problem of finding an electromagnetic field source.

The main purpose of this project is to find electromagnetic field sources. This

function can have many uses in the real world. First and foremost is finding

electromagnetic sources that are detrimental to communication and other types of signals

to critical operations. Most of these types of sources are called “electromagnetic

jammers” or just “jammers.” Electromagnetic jammers come in many forms and use

different techniques to stop electromagnetic signals to be received accurately. One of the

most widely used techniques is that they can produce great amounts of noise that squelch

out the signal so all the receiver sees is a great deal of static. There are currently several

methods to find electromagnetic jammers but none are automatic, most require man-

power and, some of the time, distance from the source, which decreases accuracy in

finding the source. It becomes more and more difficult to find the jammer when it is

saturating any sensors because of the power that the jammer is outputting. Basically, the

sensors become blind because there isn't any difference or gradient that can be found.

Hopefully, at this point, the system is close enough that the jammer can be said to be

located.

There are also systems available now that can find electromagnetic sources that

are not of the jamming sort. These systems usually have a beacon attached to something

that could be easily lost over a fairly large area, like an RC plane. These systems employ

the use of directional antennas that can measure RF energy and then the user walks closer

to the source and changes direction based on where the strongest signal is picked up.

These systems are very basic in concept and are used widely. The main problem with the

system is that there must be a way for the user to traverse the area between the user and

the beacon source. Of course, the difficulty of finding can be greatly increased or

decreased depending on the terrain that surrounds the source.

The approach that was used in this system integrates both these ideas to find the

source and integrates them onto a multi sensor platform, which makes for better accuracy

when finding the electromagnetic source.

1.2. History

The term MAS-Net stands for Mobile Actuator and Sensor network. At Utah

State University, many students and faculty alike have worked on the USU MAS-net to

produce a prototyping platform that can be used to test swarm, cooperative control, and

multi-sensor systems. The MAS-net has been used in other work to find the edges of dust

clouds, to test formation control, and to find and most interesting to this work, to track

light sources. The Light Taxi project was a project that implemented on the MAS-net had

to find a light source. The problem is the same as this project, except for the fact the

sources that are found in the two systems are different. The Light-Taxi work was used as

a model for finding electromagnetic sources.

1.3. Problem Statement

The source of an electromagnetic field can be found using multiple sensors and man

power. The whole process of location can be solved by the use of a MAS-net platform.

Also, using autonomous vehicles—especially airborne ones—a fleet of sensors can be

operated on a regular basis, making location quick and adding a tracking feature, which

would be more difficult using manpower alone.

The scope of this project is to design, build, and test a prototype system that could be

incorporated into an autonomous vehicle fleet for later use. This system must be able to

locate the source. In order to do this, the system will provide communication between the

motes to relay information of field strength between the motes, coordinate efforts of

tracking, and relay the necessary information to the base station.

1.4. Summary of Design Process

The engineering approach of this project was to first understand the system that

had been implemented earlier by other students. The MAS-net platform has three new

software elements that were not familiar to the designers, TinyOS, nesC, and Robot

Commander were all learned and used in the design. One of the major obstacles was

overcoming the vast amount of code that previous builders of the MAS-net had left

behind. It was very useful to the design team to have many examples in the software to

understand exactly how nesC worked.

The second major task was to learn and understand the capability of the hardware.

The MicaZ motes made by Crossbow are also made with the application of MAS-nets

in mind. These devices have many features, such as onboard sensors, communication

capabilities, and pre-programmed drive commands. All of these features were thought

to make it possible for the design team to apply a radio frequency (RF) sensor to the

platform and have an almost complete system. This was a horrible error on the part of

the design team, but that will be further explained in subsequent sections.

After understanding the tools that were available as part of the USU MAS-net

platform, the design and integration of the sensor onto to the motes was able to be

designed. Without knowledge of the software and hardware, the design team would not

have known the most effective way to integrate our sensors onto the motes.

After integration was done, the only problems remaining were calibration of the

sensors and characterization of the system. The design team designed a series of tests to

understand the readings that the system read from the sensors. After several tests and

cross checks with other instruments, the design team had the necessary information to

truly implement the system.

1.5. Summary of Final Results

The final results of this project have been found to be more diagnostic in nature of

the health of the USU MAS-net platform than achieving the goal of the project. As the

system was being implemented, many set backs and unforeseen problems occurred. The

MAS-net motes themselves were found to somewhat unreliable. The robot platforms

that were redesigned for the newer motes mostly malfunctioned and did not have

sufficient documentation to fix all of the problems that were found.

It was found that the USU MAS-net platform needs an overhaul.

Despite these problems, the design team was able to partially test the

electromagnetic field finder system with some success. The system was able to locate

the desired electromagnetic field source.

1.6. Organization and Summary of Report

This report is broken up into six different sections explaining the design process of

the electromagnetic field finding project. Problem analysis explains what the basic

problem is and the design solutions that were taken into consideration for solving the

problem. The design section explains the hardware and software design of the project.

This section goes through various aspects of the subsystems that were designed in the

project. The implementation section explains how the designs were implemented and

how some problems were overcome. The testing section explains what tests were done

and how they affected the implementation of the design. The final scope section explains

what has been done on the project and the valuable lessons that were learned.

2. PROBLEM ANALYSIS

2.1. Review of Problem

Electromagnetic fields are located everywhere and at any given time are all

around us. The field spectrum of most interest to this project is that of radio frequencies.

Radio frequencies are frequencies ranging from 3 Hz to 300 GHz. The radio frequency

range is primarily used for communications. This project explores the use of robots to

locate an electromagnetic field source at a radio frequency. Antennas are the medium by

which electromagnetic waves are sent through air. Depending on the design of the

antenna, the direction of propagation varies. A near-isotropic electromagnetic source will

be used as the jamming source so that the energy of the field will be propagated in all

directions equally on the plane of interest. An example of an isotropic source is shown

below in Figure 1.

Figure 1: Example of an Isotropic Electromagnetic field source in the xy-plane

As can be seen in Figure 1, the field is isotropic in the xy-plane. The use of an

isotropic field source can greatly reduce the complexity of algorithms and reduce the

number of robots needed to find the electromagnetic field source. This is because by

assuming equal propagation, the algorithm doesn’t have to change based on the direction

that a mote is approaching the source.

This simple case is used to mimic the real world application of locating jamming

signals sent out to disrupt communications. Modern communication jamming equipment

is technically very complicated and too large a magnitude for a senior design project.

Although current jamming equipment may be using complicated modern technology, the

idea behind communication jamming is rather simple. Signal communication is

dependent upon having the information sent through the air, being at a higher energy than

the energy of the electromagnetic noise of the environment. In order to disrupt

communication, electronic jamming equipment could send out another signal of high

energy that effectively increases the environmental noise with respect to the actual signal

trying to be received. This is thought of as lowering the signal-to-noise ratio of the signal

trying to be received. The signals sent out by jamming equipment may vary, but the

principle remains the same. For simplicity, the source used in our experiment will be

operating at a fixed frequency in order to provide a simple case that will be able to

showcase the method used to find an electromagnetic field source.

The sensor used must be able to detect differences in the electromagnetic field.

The sensor used to detect the electromagnetic field is obviously an antenna itself, with the

same design parameters as the antenna used to create the jamming signal. The reason for

this choice is because an antenna with the same parameters will receive a maximum

energy from the jamming signal and still be isotropic in the plane of interest. This means

that the information received by each robot can be interpreted in the same way as if it had

sensed the information, with an obvious offset due to distance of course. The method

used for finding this electromagnetic field source is through the power received by

sensors. An electromagnetic field’s energy will increase as the distance decreases. By

using this property and multiple sensors, it is possible to locate the source in an

inexpensive and effective manner. The sensor will be an off-the-shelf receiver set to

receive at the same frequency as the electromagnetic field source. The key element to this

component is the Received Signal Strength Indicator (RSSI) pin. The RSSI pin outputs an

analog voltage that is proportional to the strength of the signal received.

Cooperative control is integral to this design. The motes or agents need to work

together to find a solution to the problem. One mote by itself would find it practically

impossible to find the source. By communicating information that is known by one mote

to the rest of the motes or at least to its nearby neighbors, the electromagnetic source can

be found more efficiently and quickly. During the design, it was kept in mind that

information sharing was key to the success of the system's objective. Also, it is worthy to

note that cooperative control allows the constraints of the individual motes to be

loosened. The motes do not need to be loaded down with many sensors, only a few. The

best part of this approach is that it simplifies the motes and brings the focus to the group

of sensors.

2.2. Design Considerations

In implementing any system, there are many problems that can arise. Some of the

hardware problems that we have made considerations for are power constraints,

saturation of the electromagnetic sensor, and an electromagnetic field noise due to the

ambient environment.

The MAS-net system is designed to be low power. This is one of the key features

that make the system cost-effective, small-scale, and useful, using swarm technology.

Since this is an ideology and because the system bus has already been designed and this

is a sensor that must be integrated into a functioning system, low power is a design

constraint that must be met. The simplest way to meet this requirement is to find a sensor

that meets this requirement. There are many off-the-shelf components that can be found

in order to meet low power design specifications. The sensors that were decided upon can

be easily integrated into an existing system and meet low power specifications.

The sensor will be a Parallax 433.92 RF Receiver, which meets low power design

criteria by only operating a 5 V with an operational supply current of 5.2 mA. In addition

to the sensor needing to be low power, there are electronics that provide signal

conditioning and power conditioning in order to properly interface the sensor to the robot

platform.

The additional hardware also had to be taken into account in power usage. For

this reason and to lower costs, the power conditioning circuit that is used is a linear

regulator. A linear regulator uses little power and will condition the 6 Volt bus used by

the robots to 5 Volts used for the sensor. The linear regulator was found to be a low

power and cost effective option. The signal conditioning circuit is an op amp that will

provide a gain to the RSSI pin output in order to allow the analog-to-digital convert on

the MicaZ mote to read the data. This circuit is also low power and will not be a

significant strain on the batteries.

The saturation of the sensor used is due to that fact that the Received Signal

Strength Indication pin outputs an analog voltage that represents the signal power

received. Because the experiment will be taking place in a small confined area and the

electromagnetic jamming signal was made to operate with ranges of over 200 meters.

This presents a problem with saturation of the sensors receiving the signal. In order to

mitigate this problem, it was decided that the jamming signal be attenuated by placing a

potentiometer at the output before the antenna. This is not the most effective way to

attenuate a signal and in actual application this would not be implemented as we would

not be in a confined area. The use of a resistor should be sufficient to lower the output

power of the jamming signal and therefore allow the RSSI pin to read values based on the

distance between the source and the sensor and not a constant value giving no

information on whether you are closer or farther away from the source.

The last hardware consideration was due to the noise of the environment. This is a

problem that can be very difficult to solve. The only way to have no outside influences

that are considered to be noise is to do all experimentation inside an anechoic chamber.

An anechoic chamber uses the principal of a Faraday cage, which blocks all

electromagnetic waves. This would be an optimal situation that would enable isolated

initial experiments to be performed and have all instruments calibrated. Since this was

not possible, the next option is to mitigate such influences. One method that was used

was to choose an operating frequency that has little “traffic”; in other words, there is little

use of the frequency range that would cause unintentional jamming or disruption. The

frequency decided upon was the 433.92 MHz frequency, which is in the Amateur Radio

band. This frequency is traditionally used for amateur satellite communications. Due to

the fact that this radio frequency is not used commercially, it is believed to be an

acceptable frequency that should mitigate noise interference. On the other side, the

jamming signal that the experiment is using should not be sufficient to be in conflict with

any FCC regulations or interfere with any amateur band satellite communications.

One of the software design considerations was that the motes do not have

powerful processors. This forces the design of all algorithms to be basic and simple. The

low complexity of algorithms lends itself well to the swarm and cooperative control

method that this design is trying to employ. It was made apparent that the algorithms

needed to be kept simple for another reason besides that the motes themselves have a

great many things to control. For example, at any given time the motes need to

communicate their position to the base station, receive information from the base station

and fellow motes, read sensor data, control the motor drives, and decide what to do to

find the EM field source. This is too much to do for a low power Atmega processor with

only 512K RAM to work with to take measurements.

Another design consideration and constraint was the size of memory that was on hand

to store the program on the motes. The MicaZ motes only have a capacity of 128K for

measurements. This again forces the complexity of the algorithms and the program to be

not as complex and bug-proof as the engineers would have liked. This requires clever

design to make the decisions that the motes make themselves the best possible decisions.

2.3. Summary of Specifications

The following list of specifications is specific to this system and to this experiment.

These specifications are constraints by the MAS-net system being used and the behavior

of the sensors being used. These specifications are necessary for successful operation and

therefore must be met. Below is a list of such specifications:

• Motes must be programmed using nesC • Motes must run TinyOS • System must be integrated into Robot Commander • EM Source must not have saturation zone of less than six feet The motes that are used in the MAS-net platform must be programmed using nesC.

This specification is not flexible because the MicaZ motes have been designed for this

programming language. If nesC wasn’t used to program the motes, there wouldn’t be

enough space on the MicaZ mote to store and run the program.

The MicaZ motes were also designed to with TinyOS in mind. TinyOS is really a

small version of Linux. This event-based, driven OS is very small and allows the use for

programs written in nesC. Using this OS, it will be possible to run all the functions that

are necessary to the motes.

In order for there to be a saturation zone of less than six feet, the electromagnetic

jamming source must be attenuated sufficiently. This is an important specification for this

experiment because the size of the arena that the robots are located in is quite small.

There may be times that the robots are within six feet and they may not have located the

source. This would mean that, if the sensors became saturated and were at a distance

farther than six feet, they would think that they had found the source or become confused.

In actual circumstances, six feet would be more than ideal for a saturation region.

3. Design

3.1. Hardware The hardware design’s purpose is to integrate the EM field sensor into the MAS-net

motes and robots. This was done using the available information from both the MicaZ

mote and robot schematics and the specification given by the sensor itself. Because of

constraints given both by the mote and robot electronics and the sensors input and output

requirements, two circuits had to be designed in order to interface the sensor to the

robots. One was the power conditioning circuit and the other was the signal conditioning

circuit. Figure 2 is a high level diagram showing the flow and location of these circuits

with respect to the robot electronics and the MicaZ mote electronics.

Figure 2: High level flow diagram of sensor and interface

This system will be explained in more detail in following sections. There will also be

sections explaining the design choice for the electromagnetic field source (EM Jammer)

and the antenna attenuator used on the source. These sections will be divided as follows:

• Motes and Robot electronics

• Sensor

• Power Conditioning

• Signal Conditioning

• EM Source and Antenna attenuation

3.1.1. Motes and Robot electronics

The MicaZ motes and the Robot platforms were already designed, but in order for the

sensors to be interfaced into the system, the mote and robot electronics had to be

understood. The schematics used to interface this experiments’ electronics can be found

in the appendix.

Previously, the robots were designed to use a different mote; when the motes were

upgraded, the robot designs had to change as well. Instead of redesigning the robot

electronics, the old robot platform was modified in order to be integrated with the new

MicaZ motes. The problem was that the changes made were not documented well, which

left little knowledge as to what changes were made. All documentation available was of

the old robot platform. Fortunately, the most important information needed was location

of connectors for power and an analog-to-digital converter (ADC) pin. It was thought that

some electronics on the robots had been implemented because of the false

documentation, but on closer inspection of the boards, many of the electronics for power

were not implemented. This allowed us to find where the power electronics were and find

the connector where the batteries connected to the board. The ADC was located as a

connector that was once used as a rear IR sensor. This made it rather simple to connect to

and then use software to collect the needed RSSI pin data. The connectors were found to

be J6 for the 6 Volt bus and J5 for the ADC pin.

3.1.2. Sensor

The sensor is a Parallax RF 433.92 Receiver. The pins that are useful to this

experiment are primarily the Received Signal Strength Indicator (RSSI) pin, and the

power and ground pins. The RSSI pin will provide an analog voltage signal that will

represent the power received by the receiver. This pin must be interfaced to the MicaZ

mote’s processor through the ADC so that the analog data can be represented digitally.

Once this data is received, there may need to be an offset subtracted away representing

the noise. This sensor is easily interfaced with electronics, as shown below in Figure 3.

Figure 3: Receiver Pin out

As shown in Figure 3, the voltage required is 5 Volts. There is no 5 Volt bus located

on the robot platform; therefore, there must be some power conditioning used on the

signal before the sensor is interfaced into the robot platform. As will be shown in more

detail, both the RSSI and power pins will need circuitry to interface them into the robot

platform.

3.1.3. Power Conditioning

Because of the mismatched in voltage supplied by the robot platform and the voltage

required by the sensor, a power conditioning circuit is required. There are many ways to

adjust the voltage in a circuit. The method used in this circuit was a linear voltage

regulator. This particular circuit is well-suited for this application because it uses low

power and has acceptable tolerances. The particular chip used was a TPS76350 Low-

Power 150 mA Low-Dropout Linear Regulator. The linear regulator is very flexible in

terms of input voltage and is able to supply more than enough current for this application.

The input voltage range is 2.7 V to 10 V with a maximum supply current of 150 mA. The

sensor requires only 5.2 mA during operation. The output is very good as well, with

output current ranging from 1 mA to 150 mA and a minimum output voltage of 4.8 V and

a maximum output of 5.2 V with the typical output voltage of 5 V. This is a tolerance of

4%, which is acceptable. Figure 4 shows the design of the power conditioning circuit.

Figure 4: Power conditioning circuit

As shown above in Figure 4: Power conditioning circuit, the circuit is always

enabled by having the enable pin tied to the input voltage. The enable pin allows a

voltage range of -0.3 V to the input voltage + 0.3 V. It is acceptable, therefore, to connect

the enable pin to the input voltage, turning on the regulator anytime the robot platform is

on. The capacitor connected between the output and ground is commonly used in linear

regulators in order to stabilize the internal loop control. The capacitor on the input is used

as a low pass filter for noise rejection and to improve transient response.

3.1.4. Signal Conditioning Circuit

The RSSI pin provides an analog voltage that represents the signal power received.

This voltage must then be sent to the ADC and be read and analyzed by the processor.

The processors analog-to-digital converters must receive analog voltages in the range of 0

V to 3 V. the saturation voltage found on the RSSI pin was approximately 2 V. In order

to get the full resolution and make use of all 10 bits of precision given by the MicaZ

ADC’s, a gain of 1.5 is needed. In order to achieve this calculated gain, a non-inverting

op amp circuit is used. Figure 5: Signal conditioning circuit is the schematic used for a

non-inverting op amp configuration.

Figure 5: Signal conditioning circuit

The resistor values were calculated using the following formula for a non-inverting

op amp.

5.120000

2000010000

2

21 =+

=+

=Z

ZZK

The following gain will make use of the full range of the ADC and provide the maximum

resolution available from the ADC. Without making full use of this range, truncation

errors will occur that will make it difficult to distinguish between small distances. Due to

the confined space for this experiment, these errors could even make it difficult to detect

large distances with in the arena. Using the full range and therefore the most precision

available from the ADC’s, this will mitigate any truncation errors received from the RSSI

pin.

3.1.5. EM Source and Antenna attenuation

The electromagnetic source that will be providing the communication jamming signal

was specified to have an isotropic field pattern in the plane of propagation. This is

achieved using a monopole that is in a vertical orientation as shown in Figure 6: EM

Source.

Figure 6: EM Source

The EM source and the sensor used to detect the EM source are made by the same

company; both operate at the same frequency. This is a Parallax RF 433.92 MHz

Transmitter. The EM source has also been designed for flexibility and a variety of

applications. The pin out is shown below in figure, shows available pins and details the

use of each pin.

Figure 7: EM source pinout

The pins used in this experiment will be the DATA, power, and ground pins. The power-

down pin is left floating and therefore the system is on when power is applied to the EM

source through the 5v power pin. The power and ground pins are connected to a power

supply and the voltage is set to 5 Volts, as specified by the data sheet. The DATA pin is

set to a logic high input in order to have maximum power output sent and for simplicity.

By providing a steady power output, the motes that are trying to locate the EM source

will more easily get consistent data for calculations that are necessary for location. Due to

the output power of the EM source and the saturation of the sensors being used in close

proximity. It was decided that the transmitter output needed to be attenuated for this

experiment. The method for attenuation is the use of a potentiometer that may be adjusted

to achieve proper attenuation during experimentation. This is not a design criterion that

can be calculated; therefore, the correct potentiometer value had to be found using trial

and error. The potentiometer is placed between the antenna and the output of the

transmitter chip. This attenuation approach may not be considered the most efficient, but

due to the fact that it is not for actual implementation and is used solely for this

experiment in order to provide a basis for the approach, it was considered acceptable.

3.2. Software

3.2.1. NesC

The main language that was used in this project was nesC. NesC is an extension of

the program language C and was designed to be run in TinyOS. NesC was especially

engineered to be used where space and computing power were limited. One of the ways

that this is accomplished is through the reuse of code in the program. Basically, the code

blocks are used over and over again in the same program, cutting down program size.

NesC was also designed be run on TinyOS which is an event-driven based operating

system that has sensor networks as the primary use. NesC and TinyOS go hand in hand.

3.2.2. Finding Algorithm and Control Loop

The main purpose of the project is to find electromagnetic field sources. There are

constraints that needed to be kept in mind as the design was done. First and foremost was

what does the mote know or what does the mote need to know so that it and the system

can perform its function. The motes have only one sensor to tell where the

electromagnetic source is. Only one sensor doesn’t give any information as to where the

source actually is. It does correlate on how far away the source might be. Another key

fact about the motes is that they know where they are, which is very important when

coupled with the sensor data.

The finding algorithm is based off these two key pieces of data. As soon as the mote

is initialized and told to begin seeking, it immediately takes sensor data off the

electromagnetic field sensor. This data is transmitted to all other motes. When all the

motes have the location and sensor data, they determine which pieces of information are

valid or invalid. How they determine whether the data is valid or invalid is based off of

predetermined calibration readings. The calibration readings are analyzed so that a noise

floor is calculated. The line between valid and invalid data is then set just above the

noise floor. Though not realized in this project, the invalid data could become very useful

to the other motes as it can be an indicator to the other motes about where not to look. Of

course, this may backfire if the sensor were to be damaged in any way and thus gave a

false negative reading. This type of error can easily be overcome with more motes and

majority rules set into place. After the validity of the data has been checked, calculations

can begin on the location of the electromagnetic field source. Calculations are

straightforward. The source is modeled as an isotropic and for this use, the platform is on

a two dimensional plane. Modeling the plane only on two dimensions makes the

computations even simpler, as we can model the source as a circle. The radius of the

circle is dependent on the inverse amplitude of the signal. Thus, as the signal increases,

the calculated radius decreases. Thus, it is easily seen that the source, once properly

calibrated, can be found. All that is required is at least two sensors so that the

possibilities can be narrowed down. Three sensors would be the minimum ideal for

location; more would just add to the accuracy. After the location of the source has been

postulated, the motes then move closer in the direction of the calculation and a new

sensor reading and cycle begins a new.

3.2.3. Robot Commander Add-in

Robot Commander is PC application that allows for communication with the base

station mote. It also adds several important functions that allows for easier monitoring

and debugging of the entire system. The only thing that needs to be added to the Robot

Commander is to program the GUI of the Robot Commander to send the command to the

base station to start searching for the electromagnetic field source. The base station will

then command all of the other motes to begin this process. The only real design to this is

to allocate a lookup code for the function for Robot Commander’s and the base station’s

program code.

4. Implementation

4.1. Hardware

In order to interface the EM sensor, the circuits were combined. This gave a full

hardware systems’ view and the necessary tasks needed to implement the system. In

Figure 8: System schematic,the full system design is shown.

Figure 8: System schematic

Figure 8 shows the required design of the system in order to integrate the

electromagnetic field sensor to the robots. This design was then implemented on a small

PC board where all of the components were soldered together or to a connector that

interfaced to the sensor and the robot platform. In Figure 9: System hardware, the final

design of the hardware is complete and ready to be interfaced to the robot platform.

Figure 9: System hardware Figure 10: Integrated system hardware shows the system interfaced to the robot

platform and ready for testing.

Figure 10: Integrated system hardware

4.2. Software

The implementation of the software went somewhat according to plan. Using the

previously written code as a model and the design algorithm explained in the previous

section, the implementation went well. There were some set backs as only one of the

motes is currently working. The implementation had to be changed for finding the

electromagnetic field source. Basically, the missing data had to be hard-coded into the

sensor that actually worked. From using this quick implementation, the electromagnetic

source was able to be found.

5. Testing

5.1. Hardware

During component testing of the EM field sensor and the EM field source, it was

discovered that the RSSI pin on the EM field sensor was saturating at a voltage of

approximately 2 V. This prompted further testing and design. It was then decided that in

order for this experiment to be successful, it would be necessary to attenuate either the

output of the EM field source or the input of the EM field sensor. The easiest and most

consistent method would be to attenuate the field source due to the fact that there will

only be one and because if the field sensors were to be attenuated, it would be nearly

impossible to attenuate the equally.

Once the attenuator was designed and implemented, further testing was done. Testing

was unsuccessful. It was difficult using the instrumentation to get proper data on the

RSSI pin, due to the fact that digital multimeters were used to detect changes on the RSSI

pin. It was difficult because of the limited distance the sensor was able to move and

because of the large variations for the readings. It was decided to implement the system

and to try to verify results during testing of the robots. This would enable use of software

for averaging and use of a log scale. Before this testing could be accomplished, the full

system design had to be implemented. This required further testing of the power

conditioning circuit and the signal conditioning circuit. Testing on the power and signal

conditioning circuits was performed separately.

The power conditioning circuit received 6 volts from the robot platform and was

required to output 5 volts with a tolerance of 4%. The output was higher than expected,

with a value of approximately 5.4 volts. This is an additional 4% off of the maximum

output expected. Due to the variability of batteries, this was an acceptable result as it still

fell within normal operating conditions for the EM field sensor.

The signal conditioning circuit was designed to have a gain of 1.5 in order to make

use of the full range of the ADC’s. During testing, the results were as expected and the

gain was close to 1.5.

The testing of both the power and signal conditioning circuits was found to be

acceptable and it was decided that they be implemented into the system for further end-to

-end testing with the sensor.

Once implementation of the hardware was complete, system level testing began.

These tests provided necessary information needed to determine whether the RSSI pin, in

a small confined area, would be a viable option for locating an EM source. It must be

further noted that due to noise received by the EM field sensor, the gain would have to be

varied in future experiments involving EM field location, using the MASnet system. This

may be contributing to saturation of the RSSI pin, as it can vary both by location and

time. After testing, the sensor using different potentiometer values was still found to be

difficult to verify a distance away from the source and determine the location of EM field

source. This could be due to the fact that the EM field power does not fall off at a rate

that can be easily detected over short distances even with attenuation present on the

output of the electromagnetic field source or communication jamming signal.

5.2. Software

Testing of the software was easily done with the Robot Commander PC program. It

was easy to read the data for the sensor by passing the values into Robot Commander.

After it was seen that the sensor data was captured correctly, the control algorithm and

finding function was then tested to see if the logic was correct. Basically, it was the final

tests to ensure the system worked.

6. Final Scope of Work Statement

6.1. What has been done

The electromagnetic field finder was able to be partially brought online. Much of

the groundwork has been laid to continue with this project and to make it function

completely.

6.2. Lessons learned

The lessons learned were many. Here are few of the things that the design team

has learned in the process of designing, building, and implementing the design of the

system.

• Documentation: If there was anything that the design team wanted more, it was

documentation on what was done in the past on the MAS-net platform. A lot of

time was wasted coming up to speed or to a point of understanding that would

allow the project to go forward. The design team found no real schematics of the

MicaZ robot platforms and the comments in the Robot Commander program were

very lacking.

• Scheduling: The design team found that the initial schedule that was made was

optimistic. It seemed that set back after set back delayed the progress of the

project. Delays made it so that thorough testing was not possible.

• Time: The design team also learned that time is a very valuable commodity and

that sometimes being able to use it effectively wasn’t possible due to the lack of

understanding of the system between team members. It is very important that the

entire team has a good grasp on system function when the system is small enough

to allow such comprehension.

6.3. Future design considerations and revisions

There are many design considerations that can be made in the future. First of all, the

MAS-net platform itself needs an overhaul. As stated earlier, only one fully functioning

robot platform was available for use and, with such a lack in documentation, it was

practically impossible to fix and upgrade the rest of the robot platforms. Concerning the

functionality of the motes, the design team believes that this can be simplified to be more

efficient and readable for future users.

Other than upgrades, the design team agrees that using directional antennas is a good

next step that should be implemented and tested on the platform. Also, using this system

to be placed on UAV’s would be a great field test application.

7. Project Management

In this section, the schedule and the budget are listed. The project ran on schedule

until the implementation portion. There were many bugs and other set-backs, due to the

MAS-net platform’s ill documentation and upkeep. The project team was able to

partially recover from this set back. The budget listed was the real budget and was not

exceeded.

7.1. Scheduling

Gantt Chart

7.2. Cost

Items Cost Quantity Total Cost Parallax Transceiver Package (2 Tx & 2 Rx) $109.95 1 $109.95

Parallax Receiver $39.95 2 $79.90

Sensor Integration Circuit $4.75 4 $19.00

Engineering Hours $0.00 290 $0.00

Project Total: $208.85

8. Conclusion

As stated earlier, the final results of this project have been found to be more

diagnostic in nature of the health of the USU MAS-net platform than achieving the goal

of the project. The MAS-net motes themselves were found to be somewhat unreliable.

The USU MAS-net platform needs an overhaul. Despite these problems, the design team

was able to partial test the electromagnetic field finder system with some success. The

system was able to locate the desired electromagnetic field source.

9. Appendix

Code will be added later