UBC CREST ELEC 591 --- Applied Digital Signal Processing

Dr. Ian Cumming
Associate Professor
MacDonald Dettwiler/NSERC Industrial Research Chair
in Digital Signal Processing and Radar Remote Sensing

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Synopsis

The course will review the fundamentals of Digital Signal Processing, concentrating on those topics commonly used by practising engineers. This will include discrete system representation, A/D conversion, filter design, fast Fourier transforms, interpolation and fast convolution. In this way, students will be trained for eventual industrial work in companies using digital signal processing technology in their products.

Then, industrial applications will be presented, concentrating on the digital processing of synthetic aperture radar (SAR) signals. SAR is an imaging radar, and has become widely used in remote sensing applications such as ice mapping, ocean wave measurements and land use surveys. It is a specialty of MacDonald Dettwiler, who have built 6 airborne SAR systems, and have produced 90% of the world's processing systems for satellite SARs. Canada currently operates one of the world's most advanced satellite SARs, called RADARSAT-1. It was launched in 1995, and has opened up many interesting applications and industries in Canada. MacDonald Dettwiler is now building RADARSAT-2, a more advanced verion of RADARSAT-1, with higher resolution (3m) and multi-polarization

Other applications such as GPS navigation, sonar, audio, medical imaging and communications will be surveyed, and used as practical examples of DSP applications. The MATLAB simulation language will be used for class examples, and for assignments and projects.

It is recommended that the 4th year ELEC 466 course Digital Signal Processing, or equivalent, be taken as a prerequisite. The prerequisite is not needed if the student has a good background in linear systems theory.

Index of ELEC 591 Course Description


ELEC 591 -- Course Overview

APPLIED DIGITAL SIGNAL PROCESSING

What You'll Learn:

    1. Fundamentals of analysis of discrete-time systems, including sampling

    2. Theory and use of Discrete Fourier Transforms and convolution

    3. Design and application of digital filters

    4. How to process digital SAR radar data

    5. Introduction to other applications, e.g. audio (CDs), the GPS system, wavelets, CDMA communications, and image interpolation and data compression


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TOPICS COVERED in ELEC 591

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  1. Discrete-time Signals
    • signal representation
    • concept of filters
    • convolution
    • stability & causality

  2. Introduction to the MATLAB Simulation Language
    • variables, vectors & matrices
    • statements, operators
    • math & signal processing functions
    • for, while loops
    • printing, storing data
    • `m' and `met' files
    • plotting and printing graphs
    • compiling MATLAB code

  3. The z Transform
    • uses, definitions
    • region of convergence
    • inverse z transform
    • linearity, shift, convolution
    • multiplication, complex conjugation
    • Parseval's relation

  4. Input-Output Relationships
    • system function
    • poles and zeros
    • frequency response
    • filter examples
    • state variables

  5. Discrete-Time Networks
    • signal flow graphs
    • cascade & parallel networks
    • transpose networks
    • stability, linear phase
    • more filter examples

  6. Sampling of Signals
    • Nyquist theorem
    • aliasing
    • D/A conversion

  7. Interpolation & Decimation
    • seen as a filter design problem
    • role of FIR filters

  8. Discrete Fourier Transform
    • definition, properties
    • zero padding
    • linear convolution
    • leakage, windows

  9. FFT Algorithms
    • decimation in time
    • real-valued data
    • radix 4 FFT
    • prime factor algorithms
    • 2-dimensional DFT

  10. IIR Filters
    • mathematical structure
    • design by transformation
    • Butterworth, Chebyshev, Cauer designs
    • recursive implementations
    • ladder & lattice structures

  11. FIR Filters
    • mathematical structure
    • design by windowing
    • Parks-McClellan algorithm
    • frequency-domain design
    • non-recursive implementations

  12. Introduction to Radar Systems
    • range and Doppler concepts
    • surveillance radar
    • imaging radar
    • synthetic aperture radar (SAR)

  13. Use of DSP in Radar
    • complex signals, 2-dimensional signals
    • matched filtering
    • fast convolution
    • side-lobe control @ windows

  14. Other examples, selected from:
    • application of wavelets to signal processing
    • Global Positioning System (GPS)
    • sonar beamforming
    • DSP in compact disk players
    • the polyphase filter
    • image data compression (DCT & VQ)
    • image interpolation
    • medical imaging (CT, MRI)
    • speech processing


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COURSE READING MATERIAL Return to the INDEX

Course book for main topics & assignments:

Recommended books for extra detail on DSP theory:

To run MATLAB on your home PC:

MATLAB references:

      MATLAB Users & Reference guides (in ECE office)

      Mastering MATLAB 7
      Hanselman & Littlefield
      Prentice-Hall, 2005

      MATLAB Manual, Signal Processing Toolbox
      The Mathworks, Inc.
      South Natick, MA.

Sources of Signal Data and Projects:

Other references:

      IEEE Transactions on Signal Processing

      IEEE Signal Processing Magazine


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Miscellaneous Notes

Allocation of Marks:

33 % weekly assignments
33 % mid-term or final exam
34 % computer DSP project

A 2 % bonus may be assigned to students who contribute to class discussions on a regular basis.

Assignments: are to be handed in by 5 pm the day before the next class, in the EECE 591 box on Level 3.

Communications: All notices will be distributed by e-mail.

Prerequisite:

      The normal prerequisite to ELEC 591 is ELEC 466 or an equivalent undergraduate DSP course. Students who have not taken an undergraduate DSP course may be able to follow the material, if they study the theory part of the course carefully.

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Links to Associated Pages:




ELEC 591 Course Description / UBC / Revised: March 29, 2003