TEAM 1904 Enhancing Software Defined Radios for Underwater Acoustic - - PowerPoint PPT Presentation

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TEAM 1904 Enhancing Software Defined Radios for Underwater Acoustic - - PowerPoint PPT Presentation

Dec 23, 2022 105 likes •505 views

TEAM 1904 Enhancing Software Defined Radios for Underwater Acoustic Modem Sponsor The MITRE Corporation Faculty Advisor Dr. Peter Willett Team Members Hunter Malboeuf (EE), Davis Meissner (EE), Greg Palmer (CMPE) 00 Outline Outline 1.

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TEAM 1904

Enhancing Software Defined Radios for Underwater Acoustic Modem

Sponsor The MITRE Corporation Faculty Advisor Dr. Peter Willett Team Members Hunter Malboeuf (EE), Davis Meissner (EE), Greg Palmer (CMPE)

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Outline

00

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Outline

  • 1. Project Goal
  • 2. Background of Underwater Communications
  • 3. Project Requirements
  • 4. Project Components
  • 5. Elements of a Communication Scheme
  • 6. Project Phase Descriptions
  • a. Simulation (focus of this semester)
  • b. Hardware Integration
  • c. Analysis of Received Waveform
  • 7. Schedule
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Project Goal

01

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Project Goal

  • Develop an underwater acoustic communication system using two

Software Defined Radios

  • Initial goal is one-way SDR communication system
  • Stretch goal #1 is to add equalization properties
  • Stretch goal #2 is a two-way SDR real-time communication system
  • Three phases:

○ Simulation ○ Hardware Integration ○ Analysis of Received Waveform

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Background

02

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Background

  • Over 70% of the earth is covered

by water

  • The ocean is a 3 dimensional

space - 11,000 meters at its deepest

  • Only 2-3% is explored
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Unmanned Vehicles

○ Autonomous underwater vehicles ○ Remotely operated vehicles ○ Hybrid underwater vehicles

Manned Vehicles

○ Small research submarines ○ Large military platforms

Applications

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Why Acoustic Communications?

  • Radio Frequencies (~1m range)

○ Absorbed by seawater

  • Light (~100m range)

○ Strong dependence on water clarity

  • Ultra Low Frequency RF (~100 km)

○ Massive antennas (kilometers long) ○ Not practical outside of Government use

  • Cables

○ Expensive to lay & impractical for mobile units

  • Acoustic Communications (~1 km)

○ Affordable, low power, and well studied

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Underwater Communication Challenges

  • Multipath effects – transmitted messages bounce off the sea surface and

bottom, arriving at the receiver at different points in time

  • Power losses over the path depend on water temperature and depth of
  • peration for the transmitter and receiver
  • Doppler spreading due to transmitter and receiver motion

*Controlled environment of this project allows for AWGN channel to approximate some of these effects

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Project Requirements

03

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Project Requirements

  • Transmit and Receive small text messages in underwater environment

○ Using ASCII encoding for text, but potential to extend to other types of data (.jpg, etc…)

  • Focus on Waveform Development

○ Modulate using differential phase shift keying (DPSK) ○ Error correction to compensate for errors caused by channel ○ Interleaving to redistribute bits across waveform ○ Synchronization between transmitter and receiver to determine start of message signal.

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Differences from Previous Years

  • 2017

○ Used BPSK modulation in GNURadio ○ Different synchronization system ○ No error detection or correction

  • 2018

○ Developed channel emulator to model effects of the underwater system

  • n the signal.
  • 2019

○ Developing DPSK modulation (C++) with error detection and correction. ○ Use underwater test results to validate the channel emulator.

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Project Components

04

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Components

  • Three Ettus X310 Software

Defined Radios

  • Two acoustic hydrophones
  • Preamplifier (for received signal)

Ettus X310 Software Defined Radio [1]

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Components

  • Host machines to interface

between SDRs:

  • Three embedded processors

(Udoo X86)

*Components are MITRE provided

Udoo X86 Embedded Processors [2]

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Elements of Communication

05

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Block Diagram

Signal Source Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression Channel Effects/ Transmission Carrier Removal Bit Decision Reverse Permutation/ Interleave Decoding De- compression Received Signal Matched Filtering

  • only if time permits
  • complete
  • to be completed
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Compression

  • Encodes information into fewer bits than the original message
  • Source encoding will be done before our message signal is sent
  • Source decoding is applied after the signal is received
  • Lempel Ziv possibility

○ may not be of much benefit for our small data and ASCII messages

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

010100111001010011010 010100111001010011010

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Error Detection/Correction

  • Detect & correct errors that occurred during transmission
  • Hamming Code (7, 4)
  • Cyclic redundancy parity check will check validity of overall message

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

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Interleaving

To mitigate against sporadic bursts of noise, interleaving is used

Original data example: 00000000111111110000000011111111 Interleaved example: 01010101010101010101010101010101

This way corrupted bits are more often able to be recovered from the Hamming encoding scheme

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

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Modulation

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

  • Varying our waveform with the information in our message by modulating our

carrier signal

  • Replaced original BPSK modulation with a noncoherent Differential Phase Shift

Keying (DPSK) scheme

[2] Example of DPSK from tutorialspoint.com

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Modulation/De-modulation

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

  • DPSK implementation
  • 10 kHz carrier

frequency

  • Sampling rate 96 kHz
  • Symbol rate 4 kHz
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Frequency Shaping

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

  • Root Raised Cosine Filter
  • Current use in our code was provided by MITRE
  • Used instead of rectangular filter to reduce intersymbol interference

[3] Frequency response of raised cosine filters wikipedia.com

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Carrier Shift

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

  • Stretching or compression of waveforms in transmission
  • Doppler effect from transmitter and receiver moving

[4] Doppler effect kisspng.com

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Synchronization

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

  • Transmitter and receiver need to establish a synchronized clock to

be able to properly interpret any incoming messages

  • Transmitter will transmit a preamble chirp signal that is gradually

increasing in frequency that the receiver can lock onto and be ready to receive message in sync with transmitter

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Chirp Signal

Error Control Coding Permutation/ Interleave Modulation Frequency Shaping Carrier Shift Compression

  • Our chirp currently sweeps from 10 Hz to 2kHz over 2.5 milliseconds
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Project Phases

06

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Simulation - Completed

  • MITRE provided starter MATLAB acoustic communication system

tool

  • MATLAB Tool has been modified to:

○ Transmit and receive over AWGN channel ○ Read data from a text file ○ Encode data to ASCII characters to bits ○ Apply Hamming(7,4) Code single bit error correction ○ Use matrix interleaving for bit redistribution before transmission

  • Calculate BER and plot BER vs. SNR
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Simulation - Completed

  • Changes to MATLAB model since Design Review:

○ Replaced BPSK modulation scheme with DPSK ○ Nearly integrated synchronization “chirp” signal ○ MATLAB code is currently being ported to C++

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Matlab Output

  • uncoded

* coded

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JPG with noise

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Hardware Integration

  • Visited MITRE on November 19th to tour facility and obtain

hardware ○ Learned to operate embedded processors and SDRs

  • Udoo x86 embedded processors will operate each SDR
  • Waiting on hardware integration C++ code from MITRE
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Analysis of Received Waveform

  • Relevant quantities that will be extracted from data include:

○ Bit error rate (BER) ○ Signal to noise ratio (SNR) ○ Actual data transmission and reception rates

  • Third SDR and processor will be used to apply channel effects

○ Test theoretical operation of C++ code before water testing

  • Lab data will be compared to MATLAB and channel emulator results
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Schedule

07

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QUESTIONS?

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Works Cited

[1] MITRE. 2019 Senior Design Project Outline [2] DPSK Image from Tutorials Point https://www.tutorialspoint.com/digital_communication/digital_communication_d ifferential_phase_shift_keying.htm [3] Raised Cosine Filter Image https://en.wikipedia.org/wiki/Raised-cosine_filter [4] Doppler Effect Image https://www.kisspng.com/png-relativistic-doppler-effect-doppler-radar-wave-spe- 919067/preview.html [5] Globe image https://scienceline.org/2017/04/protecting-two-thirds-globe/