The document provides details about an undergraduate project to design and test an underwater optical communication system. The project aimed to achieve data transfer rates comparable to wireless systems by using light instead of acoustic signals. The group split into hardware and software teams, with the hardware team focusing on designing an optimal optical setup and waterproof housing, and the software team analyzing data to characterize the system impulse response and determine how the signal evolved through the system. Initial tests achieved a 1Mbps data transfer rate at 15 meters, demonstrating the feasibility of underwater optical communication using the prototype system.

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ECE191: Underwater Optical
Communication
Sponsor: Northrop Grumman
Mentors (UCSD): Professor George Papen and Professor Bill Hodgkiss
Mentors (Northrop Grumman) : Naomi Ramos and Tarun Soni
January 5, 2015 ­ March 13, 2015
Group A Members:
Maryam Emadi, Daniel Peters, Dillon Quan, Alexander Ty

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Table of Contents
Executive Summary ...……..……..……..……..……..……..……..……..……..…………. 3
Introduction ...……..……..……..……..……..……..……..……..……..…………. 4
Statement of Work ...……..……..……..……..……..……..……..……..……..…………. 4
Technical Background ...……..……..……..……..……..……..……..……..……..…………. 5
System Design ...……..……..……..……..……..……..……..……..……..…………. 5
Results ...……..……..……..……..……..……..……..……..……..…………. 9
Safety and Ethics ...……..……..……..……..……..……..……..……..……..…………. 17
Conclusion ...……..……..……..……..……..……..……..……..……..…………. 18
References ...……..……..……..……..……..……..……..……..……..…………. 19
Appendices ...……..……..……..……..……..……..……..……..……..…………. 20
Figures
Figure 1 Graphical Interpretation of Entendue ………………………………………... 6
Figure 2 Block Diagram with Photos ………………………………………... 7
Figure 3 Cage System CAD Model ………………………………………... 8
Figure 4 5th Order PRBS Upsampled ………………………………………... 9
Figure 5 Reflection Gain Readings ………………………………………... 12
Figure 6 Transfer Function of System at 10dB ………………………………………... 14
Figure 7 Transfer Function of System at 20dB ………………………………………... 14
Figure 8 Optical Power vs. Operating Distance ………………………………………... 15
Figure 9 Extrapolated Maximum Range ………………………………………... 15
Figure 10 Ideal Autocorrelation of a PRBS ………………………………………... 16
Figure 11 Cross Correlation Signal Evolution ………………………………………... 17
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Tables
Table 1 Measured Gain from Optical Setups …………………………………….. 10
Table 2 Lens Distance vs. Output pk­pk …………………………………….. 10
Table 3 Collector Distance vs. Output pk­pk …………………………………….. 11
Table 4 Output Gain Dependence on Gain Setting …………………………………….. 13
Table 5 Photodetector Range vs. Bias Voltage …………………………………….. 15
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Executive Summary
In the past twenty years, there has been increased demand for high data rate
communication systems. On land, most of our communication systems use RF signals and
wireless antenna systems which are able to transmit data at high rates. For underwater
applications, acoustic modems are the most widely used wireless communication system..
Although acoustic modems have a large transmission range, data transfer rates using such
modems is limited to about 10kHz and cannot meet recent demands for the data rates
required for integrated underwater systems such as Unmanned Underwater Vehicles (UUVs),
Aquaculture, and underwater monitoring systems. By using light instead of sound as a
transmitter, one can theoretically achieve data transfer rates as high as 10MHz [1]
. To test the
feasibility and limitations of this concept, our group set up an experiment that would emulate
the ocean environment with a water tank and ground glass.
To complete the project, our group was split into two team: a hardware and a software
group. For the software team, the main goal was to analyze data from the system by
correlating Pseudo Random Binary Sequences run through different system setups. By doing
so, the software team would be able to characterize the impulse response of the system and
ultimately demodulate the signal to receive the original.
For the hardware team, the main goal was to ensure the receiver system
(photodetector) was able to receive the strongest signal from the optic as possible, and to
prepare the experiment for testing in real world conditions. A blue laser was used in lieu of
LEDs because of its superior light intensity and narrow linewidth. In order to amplify the
received light signal, several types of optical components were tested including a non­imaging
light collector and a condenser lens. In addition, a concept for waterproofing the system was
suggested as a further exercise to enable testing the receiver in different bodies of water.
Throughout the quarter, we ran tests on the overall system to determine the optimal
optical setup, the maximum distance that our receiver can receive a signal, signal bandwidth,
and an estimated data rate of the system with our experimental setup. In the end, we were
able to provide 1Mbps data rate transfer at a distance of approximately 15 meters. We were
also able to produce cross correlations on the data we have received from LabVIEW to serve
as our impulse response. This allowed us to qualitatively analyze the evolution of the signal
as it propagates through our system and eventually how to calibrate out instrument effects.
The report details our approach, system design, and some of the challenges that we
faced while constructing our prototype.
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Introduction
Radio signals and wireless antenna systems allow us to communicate and transfer
data high rates on land. Unlike air, water attenuates light signals significantly. The goal of the
project was to conceptualize an underwater optical modem that would be able to transmit at
data rates comparable to those which we achieve on land. Researching and developing
method of communicating underwater can greatly enhance the fields that require underwater
communication such as oil rig monitoring where high speed wireless communication between
the base station and the autonomous vehicle is necessary. Also, high speed communication
is a necessity for military and defense purposes which is why our sponsor Northrop Grumman
is interested in this research.
Currently, most of our underwater communications have been dealt with using
acoustic signals and modems. In water, sound can travel up to 1500 m/s which is
approximately 4 times faster than on air [7]
. However, the speed at which sound travels
through water is depended on the temperature and the salinity of the water. In fact, these
dependence also causes refraction of the sound waves causing the signal to go in different
direction which is an unavoidable defect. One of the biggest issues of acoustic modems is
that its data rate transfer is restricted to a certain speed, mainly around kbps. This is the case
because in water, high frequency sound gets attenuated at a faster rate than lower frequency
sound. As a result, there is a tradeoff between distance of the signal and speed.
A much faster option compare to sound is light. The speed of light is approximately
m/s which faster than sound. Light isn't affected from the temperature or salinity of0 3 × 1 8
water. However, it does get scattered and absorbed when brought underwater. In this paper,
we will address and demonstrate on how we rectify this issue and go through the process on
what we implemented to the receiver to enhance the signal received.
Before moving further with the design, we would like to bring up that this project was
an ongoing project that was started last quarter. With this being said, the driver circuit, laser,
and photodetector was already set by the group before us. The reason they chose to use a
laser as the light source rather than a LED was because they have a higher optical power
output and can switch faster than a LED. In addition, there was a LabVIEW code that we used
to extract data out of the computer was already written by a grad student outside of our group.
So we simply worked with the components given and optimize the overall design.
Statement of Work
The project team was split into two separate groups with different goals in mind. The
hardware team was composed of Daniel Peters, Dillon Quan, and Alex Ty. The software team
was composed of Maryam Emadi.
The overall goal for the hardware team was to prepare the apparatus for testing in real
world conditions. The group pursued three subgoals to meet this requirement: determine the
optimal optical setup for the system, design a waterproof system to house the apparatus,
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estimate optimal settings for sending signal. The optimal optical setup will consist of optical
components ordered through vendors which the team will test to determine the combination of
optical components which is able to maximally amplify the light intensity. The team will also
determine the sensitivity of the system to off­axis displacements, angular alignment, as well
as the system’s dependence on operating parameters such as bias voltage and current,
photodetector gain setting, and signal frequency.
The overall goal for the software team was to determine and characterize the impulse
response of the instruments and various system elements. To this end, the software team
gathered data from four different setups and correlated each. Utilizing mathematical tools, the
team will analyze the impulse response of the system at various stages of the evolution of the
signal. The first signal that will be analyzed is the correlation of the original signal being sent
to the waveform generator this will serve as the baseline to compare the rest of the correlation
results. The signal was then ran through the waveform generator and the digitizer. This signal
was correlated and compared to the baseline. Two more signals were analyzed; one where
the signal was taken from the waveform generator through the drive circuit to the laser and
photodetector and fed back into the digitizer, and another with the same setup but with a
ground glass diffuser between the laser and detector. The team will then qualitatively analyze
the Fourier Transform of each correlation to examine how the signal evolves as it propagates
to the system.
Technical Background
Non­imaging Collectors
In this project, we make use of non­imaging optical collectors in the hopes to increase
the amount of light that is incident on the photodetector. This type of collector is most widely
used in solar applications due to its relative pricing compared to imaging optics of comparable
size.
One trade­off in making use of non­imaging collectors is the fact that they reject a
significant amount of on­axis light rays, and even more off­axis light rays. Imaging optics have
the advantage of rejecting no light rays at all aside from reflections at the interface. However,
this is offset by the ability to upscale input diameters, limited only by the height parameter of
the setup; a quality that sets non imaging collectors apart from imaging lenses.
One of the effects of using a collector we considered is the increase in the angular
extent of the ray bundle upon exiting the collector. Entendue is conserved in any optical
system and is the product of the solid angle of incident light and the area of the aperture.
A Ω A Ω1 1 = 2 2
Because our system has lateral symmetry, we estimate the ratio of the maximum
angle of incident light to the maximum angle of output light to be
θ d d θ1/ 2 = 2/ 1
Where and are the input and output diameters of the collector respectively. Ad1 d2
graphical interpretation of entendue is produced below in Figure 1.
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Figure 1: Graphical Interpretation of Etendue
A more detailed examination on the research we conducted on optical collectors is
reproduced in Appendix A
Correlation and Pseudo Random Binary Sequences
Correlation as a mathematical tool is used in a wide variety of signal analysis
applications. In our project, we use Correlation to analyze the signal distortion due to the
instruments and more importantly the water sample through which we are sending the signal.
The correlation between two discrete signals and is defined as:f g
The result of the above equation can be thought of as a convolution without a time
reflection. A more detailed explanation on correlation is provided in Appendix B.
The signal that is sent through the system is called a Pseudo­Random Binary
Sequence (PRBS) which is most widely used in calibrating equipment against signal
distortion [3]
. It serves as a tool to measure the impulse response of a system where in any
practical application sending a short, but high energy signal is impracticable. PRBS signals
are deterministic and have a characteristic correlation function which peaks at the time index
0, resembling a delta function centered at t = 0.
We used LabVIEW to implement a PRBS of order 5 as an input to the system and
then upsampled the signal by 8 in order to increase the time for which the receiver can detect
the signal. The requisite impulse response for an upsampled PRBS resembles a sinc function.
(See Appendix C for a more detailed discussion on PRBS signals)
System Design
Overall
Our project group inherited this project from a previous ECE191 project team. Many
pieces of the system were already in place when we began our work with the system. The
main method by which we test the underwater optical modem is using a large fish tank filled
with water to simulate the medium. The signals which we send through the modem are
generated in a PXI 1044 box that houses both the waveform generator and receiver. The
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signal from the waveform generator is sent to a drive circuit that was designed by the previous
group which in turn drives the laser mounted on top of the power supply. Our receiver
instrument is a PDA36­A photodetector purchased by the previous group from Thorlabs. The
signal received from the detector is routed back into the PXI 1044 box and processed by
LabVIEW. A block diagram with pictures to accompany the existing system is produced
below:
Figure 2: Block diagram with corresponding photos of system
Hardware
We resolved to use a non­imaging optical collector in order to increase the light signal
incident on our photodetector. Three types of solar light collectors were found, so in order to
choose which to use, we used a mathematical model for each collector and compared the
gain estimates of each. Our model began by fixing the collectors’ geometric parameter maxθ
and varying the water dispersion by modeling it according to the Lambertian Model. (see
Appendix D for more detail on our model)
Using our model, we concluded a parabolic collector would be the best collection optic
for our system. The defining characteristic of an parabolic collector is its superior gain to the
others in high dispersion systems. Once we looked for commercially available collectors,
however, we found that the one that best suited our needs in terms of the size of existing
materials was an elliptical collector which has the same properties as the parabolic collector.
In order to gather the light that is dispersed through reflections in the collector, we also
selected an appropriately sized condenser lens with a low f number. The f number is the ratio
between the focal length and diameter of the lens, and indicates how well the lens is able to
focus light incident at steep angles. As we saw in the technical background, this optic is
necessary to direct as much light as possible exiting the light collector onto the photodetector
aperture.
We tested the effects of each of these components for its optimal angle and distance
from the photodetector to receive the strongest possible signal.
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With the system components decided, we ran tests on its sensitivity to relative
placement and settings on components. These include the spacing between each component,
the axial angle of the system, axis offset, and the photodetector gain setting. In order to
decrease the degrees of freedom of movement of the system and to keep all the optical
pieces on the same optical axis, we also bought a cage system shown below.
Figure 3: Cage system model for mounting inside ABS piping
Software
Purpose
Since a PRBS can be used to find the impulse response of the system, we utilized
LabVIEW code that generated a PRBS and passed it into an AWG (Arbitrary Waveform
Generator) which we used to drive our laser, simulating the transmission of data. By looking
at the re­digitized data we received on the other side, we characterized our channel’s impulse
response, and planned to remove the distortive effects using postprocessing on the
otherside. Our goal for signal analysis was to get preliminary data showing the impulse
response of each segment of our setup so that we could isolate the effect of each part of the
setup and identify which parts, if any, that create significant distortion.
Our Signal
An nth­order PRBS has a length of . For our purposes we used a 5th order 2n
− 1
PRBS, which gives us a length of 31. However, to prevent errors from small time delays, we
upsampled the PRBS 8 times so that each bit (1 or ­1) became 8 1’s or 8 ­1’s. This gave our
PRBS signal a length of 247 bits.
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Figure 4: 5th Order PRBS Upsampled 8 times
Our Setup
LabVIEW was used to generate these PRBS test signals for the waveform generator.
The waveform generator converts the input PRBS digital signal into an analog waveform and
passes the signal through the system. The data is collected from the photodetector and
digitized so that LabVIEW can be used to gather the received signal on the computer. Using
the raw data output from LabVIEW in separate MATLAB code, we compared the similarity of
input and output signal in order to calibrate the system.
LabVIEW Code Issue
Throughout the project, we used LabVIEW to gather and export data. After attempting
to correlate input and output signals gathered through the system, we realized that LabVIEW
code had an issue. LabVIEW’s buffer was overflowing, causing some of the data being read
to be occasionally “dropped”. These missing sections of data caused aperiodicity in the signal,
which resulted in graphs that do not resemble PRBS correlations. The LabVIEW code was
later corrected and we were able to reprocess the data and recovered correlations that
resembled PRBS correlations.
Results
Hardware Analysis
Optimal Optical Instruments
In order to test how much gain we received from our optical apparatus, we tested the
system using various optical instruments. Table 1 summarizes our data for the gain
measurements for individual setups. The setup descriptions are abbreviated according to the
following legend:
● L: Laser
● T: Water Tank
● G: Ground Glass (220­Grit)
● Co: Condenser Lens
● C: Elliptical Collector
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Table 1: Measured Gain from Several Optical Setups
According to the data above, the optimal setup after diffusing the light with the ground
glass diffuser is the setup using the elliptical collector and condenser lens.
Optimal Arrangement of Individual Pieces
We tested the optimum distance between the lens and the photodetector as a test to
our hypothesis that the optimal placement is at 1.2cm which is the focal point of the
condenser lens. The spacing between the components was limited by the cage system
pieces, thus our minimum distance we could achieve was at the focal point itself 1.2cm. The
data gathered from this experiment is summarized in Table 2.
Table 2: (Lens distance measured from Lens holder to Photodetector holder; Gathered at 20dB Gain setting
on Photodetector)
The data suggests that the optimal distance between the lens and photodetector is the
minimum. Unfortunately, we were unable to order a lens holder within the timeline of our
project, so we are unable to test if moving the lens even closer would result in a higher gain.
We also sought to optimize the collector distance to the condenser lens. We began
with the hypothesis that the collector distance should be nestled right up against the lens and
varied the distance to test this. The results from the experiment are summarized in Table 3
below.
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Table 3: Gathered at 20dB gain setting on Photodetector; Collector distance measured from Collector holder
to lens holder which is at minimum separation to photodetector holder.
Ground Glass
The pieces of ground glass we used both have their own gaussian distributions of
power versus angle from the point where the light hits the ground glass. The pieces each
came with a different “grit” (which corresponds to the grit of the abrasive used to change the
glass from being flat to being very bumpy on the microscopic level so that it diffuses light).
The lower the dirt number the more diffuse the simulated light source is. However, for our
measurements we wanted to ensure that our ground glass was giving use the gaussian
distribution we expected, and not some other non­symmetric function.
We tested the 220 grit ground glass that we used to simulate an ocean environment
and found that it performed very close to manufacture specifications. This means that our
assumptions that ground glass would allow us to simulate a diffuse lambertian source, which
we expect the ocean environment to be, was correct.
Reflections
One of the concerns with testing through our tank is that using a tank introduces a few
index of refraction changes that would not be present in the real ocean environment. Our
tank, which is made of plexiglass, reflected power from the air­to­glass transition and the
glass­to­water transition, and on the other side, the water­to­glass and glass­to­air transitions.
These interfaces each produce reflections which could be artificially lowering pour data for
comparing transmission through free space against transmission through water (as simulated
by the tank).
Material Air Plexiglass Water
Index of Refraction 1.001 1.488 1.33
Note: * The index of refraction of these materials can depend on temperature and wavelength of light. These are just
approximate values for estimation.
Because of the index changes it was very important to make sure the laser beam
incident on each interface was normal to the surface so that as much power as possible was
transmitted through and that the ray didn’t refract through each interface.
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We measured the power of the reflected rays in order to see how much power we
were losing purely from the non­ideal reflections.
Figure 5: Reflection Gain Readings Compared to
Transmitted Gain
Our data showed that we were losing a significant level of light to reflections through
the system. The power of the reflection off of the first tank wall constituted 15% of the total
received power. Likewise the reflection off of the second tank wall resulted in around another
5% loss. This means that we are losing a considerable amount of power to reflections.
Axial Offset Dependence
We tested our setup for its sensitivity to axis offsets. We kept the laser direction
constant, and after axially aligning the photodetector to the laser, we slowly moved the
photodetector perpendicular to the laser axis. Using ground glass, we found that the signal
strength was highly dependent on the offset to the point. A perpendicular distance of more
than 15 cm between the laser’s optical axis and the optical axis of the collection system
resulted in half the power. This means that it is important to keep the optical axis aligned in
water environments. Using a broader collector or a more diffuse source (at a higher optical
power) might mitigate this dependence.
Axial Angle Dependence
After determining the axial offset causes significant losses in our received signal, we
also tested the dependence on the axis angle. We aligned the photodetector and laser once
again and slowly turned the photodetector clockwise until no signal was received. We found
that even up to 10 degrees, the photodetector was receiving about half the signal strength as
when it was perfectly aligned. We were even able to tilt the collection system 5 degrees
before there was any drop at all. This effect disappears once the collector is removed. Our
collector is good at collecting light that isn’t perfectly on the optical axis.
Dependence on Gain Setting
Our photodetector (PDA36­A) has a dial that varies the gain setting for the incoming
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light. Because the gain setting affects the maximum signal frequency and noise amplification,
choosing the lowest possible setting while being able to receive sufficient signal strength is
the optimal solution. We first tested to see that the relative gains between setups is not
affected by the gain setting on the detector in order to make sure our assumptions were
correct.
Table 4: Testing output gain dependence on gain­setting on PDA36­A Photodetector
According to our data, the gain setting does not affect the relative gains between each setup
of the photodetector. Since 20dB has a maximum signal frequency of 1MHz and 30dB at
~500kHz as detailed on the specification sheet, we decided to keep the detector at the 20dB
setting.
The gain setting, however, does offer another variable for the system which might
allow us to boost the distance while sacrificing higher data rates. If after real world testing the
20dB setting proves to be too weak, we can switch to a higher setting at the cost of lower
bandwidth.
Signal Bandwidth Testing
In order to test the overall bandwidth of our system, we swept the input frequency and
measured the output voltage from the photodetector, holding all other variables constant. As
mentioned before, the photodetector has a bandwidth limit depending on the gain setting. To
test the effect of this setting, we recorded the bandwidth of the overall system with the gain
settings at 10dB and 20dB using a 0.5 Magnitude cutoff for either end of the spectrum. With
the setting at 10dB, the system bandwidth was measured at 10kHz to 1MHz. With the setting
at 20dB, the system’s bandwidth varied from 10kHz to 600kHz. The graphs from both
experiments are shown below.
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Figure 6: Transfer Function of System with photodetector at 10dB
setting
Figure 7: Transfer Function of System with photodetector at 20dB
setting
Although our measurements deviate from the specified maximum frequencies of the
photodetector, we believe our results suggest our system follows the specifications. The fact
that the bandwidth at 10dB was able to reach up to 1MHz and at 20dB 600kHz shows that the
driver circuit of the laser may not be the issue. From these tests, we suspect that the
photodetectors 1Mhz bandwidth at 20dB, as specified by the manufacturer, may not be
accurate.
However, despite not having ideal components, the bandwidth of our system still
outperforms acoustic data rates. Typically, acoustic modems transmit at 10kbps while our
system is able to transmit at ~500kHz shows that our system can send up to 1Mbps easily
which is 100 times faster than the typical acoustic system.
Maximum Operating Distance
In order to get an estimate how far we could transmit data we set up the collection
system in the optimal arrangement, centered the optical axis of the laser to the collection
system, and moved the receiver until we could no longer see the received signal on the
oscilloscope. We performed this same experiment for two pieces of ground glass
(representing more or less diffuse light) and three different bias voltages. The lowest voltage
our driver circuit can be biased with such that the laser remains on is around 5V. The highest
our current system can be biased is 7V. This is because the transistor in the laser driver
circuit can only handle 1W of power and at higher voltages we threaten to ruin the transistor.
However, this limitation can be removed in the future in order to produce much higher power,
if necessary. After measuring the cutoff distance for each bias we found that the distance
obtained roughly double with the increase of 1V bias. Using this relationship we predicted that
at 9V we would have a maximum distance of around 15 meters.
.
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Table 5: Maximum distance between transmitter to receiver
However, using the scope to determine maximum distance underestimates how far we
could actually go. With a good photodetector and good signal analysis we were told by the
mentor that we could detect as low as 1 uW of power. Using this as our threshold we
proceeded to make an estimate for the maximum separation between receiver and transmitter
in an optical modem underwater. To do this, we measured the behavior of the signal strength
as a function of the distance between the photodetector and a piece of ground glass. We then
converted this voltage reading to optical power using the specified efficiency for our PDA36­A
detector and extrapolated the data using an exponential function of best fit. The data we
gathered is reproduced below:
Figure 8: Data taken at 20dB Gain setting on photodetector with
220­Grit Ground Glass
Figure 9: Intersection of the extrapolated optical power vs.
distance curve with 1uW at 6.35 meters
With 7V we would be hypothetically able to receive data at 6.35 meters. Using our
rough rule of distance doubling for every 1V increase in bias suggests that our system would
be capable of receiving data from 25 meters away at 9V bias. However, we were not able to
gather data at this voltage range due to 1W limit on the transistor on our drive circuit.
Signal Data Analysis
Expected Result
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In order to determine what the ideal result would be, we used MATLAB code to
generate a Gaussian PRBS with a given mean and variance. The correlation of a PRBS with
itself results in a graph as plotted in Figure 10 shown below. A a constant low level of “noise”
along with a pronounced spike in the center. Correlation can be crudely thought of as the sum
of the overlap between the two functions. Because of the mechanics of the function, the
length of the self­correlation (or autocorrelation) of a function is 2*Length ­ 1. In our case the
PRBS length is 247, so we get a total correlation length of 493.
Figure 10: PRBS Autocorrelation result
Correlation in MATLAB
This graph was created by MATLAB’s XCORR function. It shows the amplitude of
PRBS correlation versus the correlation length in time domain. Correlation is a mathematical
formula and calculation defined by the equation in Appendix A. Since XCORR is a MATLAB
specific function and has its own method, this graph may look different if it is implemented in
other languages. The XCORR function in MATLAB has slightly different functionality in the
time domain as compared to implementations in other applications.
Test Cases
1) Case 1: Input and Input: Correlation of PRBS generated in LabVIEW with itself.
2) Case 2: Back to Back: Correlation of input and output PRBS generated from LabVIEW
sent from the AWG directly into the digitizer.
3) Case 3: Laser and Photodetector: Correlation of input and output PRBS by sending
from the laser to photodetector.
4) Case 4: Ground glass: Correlation of input and output PRBS by sending laser through
Ground Glass and photodetector.
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Figure 11: Time and Frequency Domain of each Cross Correlation in sequence
Safety and Ethics
Be it sound waves or visible light, either communication method creates disturbances
that could be problematic to marine wildlife. Many species of underwater wildlife can see
visible light and are affected by its presence. Fisherman sometimes even use laser light as a
lure to attract fish. Blue light is the color many fish see best [8]
since blue is attenuated the least
in water . Unfortunately, this means that the blue glow from the laser will be more impactful to
the environment of the marine life. The impact of laser communication is not fully predictable,
and therefore before a full implementation it would be responsible to check with a marine
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biologist to make sure that such a system would not needlessly endanger the fish population
and other aquatic life.
Lasers can be dangerous when not used properly. Since we are dealing with a
relatively powerful laser beam it is important to aim the laser such that neither the beam nor
stray spectral reflections will not end up damaging someone's eyes.
Another one of the main safety concerns is the use of electricity underwater. Our
design calls for using two 12­volt batteries to power the photodetector. These could pose
shock and contamination risk if the waterproofing fails and they were exposed to the water.
While the acid batteries claim to be “spill proof”, the leakage of any lead­acid, particularly in
marine habitats, could be harmful to the ecology.
Another potential hazard from our system is when submerging the waterproof system
down in the ocean. Since the waterproof system consists of some plastic and glass, leaving
any parts and bits of our waterproofing system will pollute the ocean and potential harm
animals that may see it as food.
Conclusion
According to our data, an optical modem can provide a data rate transfer at
approximately 1Mbps, surpassing a typical acoustic modem which can provide at most
10kbps. However, our experiments also show that the distance between the transmitter and
the receiver is much more limited compared to acoustic modems. Extrapolating from our
various test we expect to be able to successfully transmit and receive data with our system at
around 25 meters, assuming that the ocean water is well modelled by ground glass.
One of the benefits of using an optical modem is its directivity from the transmitter to
the receiver compared to an acoustic modem. This is the case because an optical laser
modem has a narrow beam of light with which to transfer information. Because of this, stray
information from communications is minimal which is useful in the case of transmitting
sensitive information. For an acoustic modem, sound coming from a transducer may refract in
a broad range due to the temperature gradients and variable salinity of water.
We have determined that the best optical system includes the collector, condenser
lens, and photodetector to recapture maximum diffused light. In order to waterproof the
system underwater an optical window between the collector and condenser lens will be used
to seal the system while allowing as much light as possible through. Our design also called for
a cage system which holds the elements in alignment. This cage system would be housed in
a 4” ABS plastic pipe with T­joint with space for the optical components and batteries for
powering the photodetector.
While we were ultimately unable to test the system in the real world, we still believe,
based on our data and experiments, that underwater optical communication using our design
is a viable option for high data rate and short to medium range communication. Our laser is
capable of outputting more power than what we have been driving it at during our tests, and if
necessary, we could replace the drive circuit for one with a higher power tolerance or increase
the gain setting on the photodetector.
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20.
References
1. Brundage, Heather. "Designing a Wireless Underwater Optical Communication
System." Thesis. MIT, 2010. Web.
2. Farr, Norman E., Lee Freitag, James Preisig, Dana R. Yoerger, Sheri N. White, and
Alan D. Chave. Systems and Methods for Underwater Optical Communication. Woods
Hole Oceanographic Institution, assignee. Patent US 20070183782 A1. 20 May 2009.
Web.
3. Maksimovic, Dragan, Regan Zane, and Botao Miao. "A Modified Cross­Correlation
Method for System Identification of Power Converters with Digital Control." 35th
Annual IEEE Power Elecrronics Specialisls Conference 35 (2004): 3728­733. Web. 01
Feb. 2015.
<http://ecee.colorado.edu/copec/paper_archives/amodifiedcrosscorrelation_jun2004.p
df>.
4. Morel, Andre. “Analysis of variations of ocean color.” ASLO, 1976. Web:
http://www.aslo.org/lo/toc/vol_22/issue_4/0709.pdf
5. Mutagi, R.N., “Pseudo noise sequences for engineers”, 79­87, April 1996. Web.
6. Stewart, Robert H. "Light in the Ocean and Absorption of Light." Chapter 6 ­
Temperature, Salinity, and Density. Department of Oceanography, Texas A&M
University, 15 Sept. 2006.
http://oceanworld.tamu.edu/resources/ocng_textbook/chapter06/chapter06_10.htm.
Web. 17 Mar. 2015.
7. Stojanovic, Milica. Underwater Acoustic Communication. Northeastern University, n.d.
Web.
8. Ross, David. "Fish Eyesight: Does Color Matter?" MidCurrent. N.p., n.d. Web. 01 Mar.
2015.
9. Winston, Roland, Juan C. Miñano, Pablo Benítez, and W. T. Welford.”Nonimaging
Optics”. Amsterdam: Elsevier Academic, 2005. Web.
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Appendices
Appendix A Non­imaging Optical Collectors
We came across three types of collectors that would help our design collect light.
These three types of collectors are compound parabolic concentrators (CPCs), conic
collector, and the parabolic collector.
Of the three collectors, the CPC has the closest to the ideal concentration ratio which
describes how much incident light is successfully transmitted at the other end. Shown below
is the transmission vs angle curve. From the graph, we can see that there is a higher range of
acceptance angle for a CPC. In addition, at specific angle of incidence of light the slope at the
passband is steep which means that the collector will not accept light rays higher than this
angle. Despite this, CPCs’ concentration ratio is the highest which makes it the ideal choice
for the system.
Transmission vs Angle curve for CPC
Compared to the CPC, the conic optical collector and the parabolic optical collector
have a lower concentration ratio, but are easier to fabricate. The transmission vs angle curves
for both the conic optical collector and the parabolic optical collector are shown below.
Transmission vs Angle curve for Conic
Collector at 10 θmax = o
Transmission vs Angle curve for Parabolic Collector
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22.
From the transmission curves shown above, one can see that the conic collector has a
rolloff that begins earlier compared to the CPC. The parabolic collector rolls off even earlier
than the conic collector, but contains a more gradual slope of at the right edge of the
passband. This implies that we could collect more light coming from steep angles using the
parabolic collector.
Appendix B (Correlation)
Correlation (or cross correlation) is a method of quantitatively measuring signal
matching. For discrete sequences, the cross­correlation between two signals is defined as
the following:
where f *
is the complex conjugate of f[m]. For the purposes of testing a single clock will
be used for both the input and received sequence. Since these two signals are synchronized
in this way, the phase shifting properties of the PRBS can be once again exploited and any
system delay can be found.
Appendix C (Pseudo Random Binary Sequence)
In order to characterize the channel and its effect on our signal, a Pseudo­Random
Binary Sequence (PRBS) is used as a test signal. A system or channel is fully characterized
by its impulse response, also called the transfer function. Theoretically one could ascertain
the impulse response by sending a delta function through the system. However, this method
is impractical because it would require a high energy and infinitely short pulse. In order to find
the impulse response of the system, one only need correlate the input PRBS with the output
signal. When correlated, PRBS signals transform into delta functions. Using data analysis it is
possible to recover the impulse response of a system purely from its response to a PRBS
signal. Specifically, if a PRBS is correlated with itself (autocorrelation) a spike at zero phase
of magnitude N = length of sequence should appear.
Appendix D Mathematical Model of Non­imaging Optical Collector
We began by assuming the light dispersion in water could be modeled as a lambertian
source corresponding to a mathematical distribution of:
(θ) I cos (θ) I = 0
n
Where n is a model parameter that controls the light dispersion.
In order to simulate the transmittance ratio of each collector, we used a logistic growth
function which we named and is modeled as such:(θ)w
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(θ) (1 (k(θ )) w = 1/ + exp + o
Where determined the steepness of the falloff and determined the location of thek o
falloff. We found that this method of altering just two parameters of the equation has limited
capabilities in modeling the effects that the transmittance graphs from Winston [9]
, so we
decided to vary the Lambertian scattering parameter n instead of testing against various
geometries of each collector.
With the models and equations in place, we structured our power estimates according to the
following function:
π w(θ)I(θ) (θ)dθPtot = ∫
π
0
2 sin
We ran the model using Python code with matplotlib and scipy as libraries to help with the
calculations and data plotting. The plotting results are reproduced below.
Red represents the parabolic collector,
Green represents the conic collector, and
Blue represents control (no collector)
Red represents the parabolic collector,
Green represents the conic collector, and
Blue represents control (no collector)
Appendix E (MATLAB Code)
input = dlmread( 'input.txt' , 't' );
back = dlmread( 'back.txt' , 't' );
pd = dlmread ( 'PD.txt' , 't' );
gg = dlmread ( 'GG.txt' , 't' );
input1 = input(:,1);
back1 = back(:,2);
pd1 = pd(:,2);
gg1 = gg(:,2);
corr1 = xcorr(input1,back1);
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corr2 = xcorr(input1);
corr3 = xcorr(input1,pd1);
corr4 = xcorr(input1,gg1);
m = [max(corr1) max(corr2) max(corr3) max(corr4)];
maximum = max(m);
subplot(4,2,1)
stem (corr2(650:1150)/max(corr1));
title( 'Time Domain of Input & Input ' );
xlabel( 'Correlation length' ); ylabel( 'Amplitude' );
subplot(4,2,3)
stem (corr1(250:713)/max(corr2));
title( 'Time Domain of Back & Back' );
xlabel( 'Correlation length' ); ylabel( 'Amplitude' );
subplot(4,2,5)
stem (corr3(1500:1993)/max(corr3));
title( 'Time Domain of Photodetector' );
xlabel( 'Correlation length' ); ylabel( 'Amplitude' );
subplot(4,2,7)
stem (corr4(1250:1743)/max(corr4));
title( 'Time Domain of Ground Glass' );
xlabel( 'Correlation length' ); ylabel( 'Amplitude' );
subplot(4,2,2)
stem (abs((fftshift((fft(y,256)/256)))));
title( 'Frequency Domain of Back to Back' );
subplot(4,2,4)
y = corr2(250:713)/max(corr2);
y = corr1(1200:1693)/max(corr1);
stem (abs((fftshift((fft(y,256)/256)))));
title( 'Frequency Domain of Input to Input' );
subplot(4,2,6)
y = corr3(1500:1993)/max(corr3);
stem(abs((fftshift((fft(y,128)/128)))));
title( 'Frequency Domain with the Photodetector' );
subplot(4,2,8);
v4 = corr4(1250:1743);
z = fft(v4,256)/max(corr4);
stem(abs((fftshift((fft(y,128)/128)))));
title( 'Frequency Domain with Ground Glass' );
Appendix F Light Attenuation in Water
Light attenuation is defined as a loss in light flux while traveling through any medium.
Light attenuation is characterized by the exponential dependence on the distance the light has
traveled through the medium [6]
. Quantitatively, light attenuation in different media is given as
the absorption coefficient, for a distance traveled .α x
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25.
I (− x) I = 0 exp α
Absorption coefficients have a dependence on wave frequency as light waves do not
all interact to the same extent in the medium. A graph of absorption coefficient vs light
wavelength is reproduced below:
Absorption Coefficient of water vs. Light Wavelength
(From Stewart, “Light in the Ocean and Absorption of Light.”)
As evidenced from this graph, we see that the absorption coefficient has a distinct
minimum close to the blue wavelengths of visible light. For liquid water, the minimum has
been calculated to be at 412nm. Aside from wave frequency, absorption coefficients vary
across water samples due to the variable turbidity, salinity, and presence of marine life.
However, this is beyond the control parameters of our system.
Appendix G Ground Glass
In our setup, we used ground glass to simulate the dispersion of water in the real
world. The following graph shows the manufacturer specifications of ground glass.
Manufacturer Specifications
Ground Glass Transmitted Power vs Angle (From Thor Labs Datasheet )
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26.
Appendix H: Parts List
Thorlabs
*Si Transimpedance Photodetector: PDA36A
1” Ground Glass Diffuser 1500 Grit: DG10­1500­MD
1” Ground Glass Diffuser 220 Grit: DG10­220­MD
Imperial Lens Mount for 1” Optics: LMR1
Photodetector Power Cable: PDA­C
Cage System
Adjustable Lens Mount 0.50” to 2.00”: LH160C
0.5” Aspheric Condenser Lens f = 8mm: ACL12708U­A
18mm Aspheric Condenser Lens f = 15mm: ACL1815­A
60mm Cage Plate: LCP09
30mm to 60mm Cge Plate Adapter: LCP02
8” Cage Assembly Rods: ER8­P4
60mm Cage Mounting Bracket: LCP01B
60mm Cage Alignment Plate: LCPA1
Edmund Optics
64mm Dia x 78mm FL Ellipsoidal Reflector: #90­968
2” Post Holder and #03­655, Post Holder Assembly: #59­006
70mm Bar­Type Lens Holder: #03­669
3” Length, ¼­20 Stud, Steel Post: #59­754
50mm Dia. Fused Silica Window: #47­230
Other Vendors
12V Motorcycle Battery
*Part purchased by previous group
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