EECE 522 Estimation Theory                                    

This Course is Offered Spring of Even Years; Next Offered Spring 2016

News & Announcements

 

Instructor Information

Administrative Handouts (pdf files)

Course Description

Addresses the theory and practice of estimating parameters for discrete-time signals embedded in noise.  Topics include:

Background Assumed

This course is not for the mathematically weak!!

Must Have a Basic Understanding of:

Textbook

Other Books of Interest   

  1. Parameter Estimation - H. Sorenson

2.     Signal Processing: Discrete Spectral Analysis, Detection, and Estimation - M. Schwartz and L. Schaw

o       Ch. 2 Reviews Digital Signal Processing

o       Ch. 3 reviews Random Discrete-Time Signals

o       Ch. 6 gives concise coverage of Parameter Estimation (Classical and Bayesian) as well as Wiener Filter

o       Ch. 7 covers Kalman Filters and has example of Aircraft Tracking

  1. Introduction to Random Signal Analysis and Kalman Filtering - R. Brown
  2. Estimation Theory and Applications - N. Nahi
  3. Applied Optimal Estimation - A. Gelb
  4. Data Analysis: A Bayesian Tutorial - D. Sivia

Relevant Papers & Other Material  

For most of these you can find them in the library.

I'll try to post most of them on Blackboard.

 

Only by reading papers in the area can you really get a feeling for how this stuff works!

The following link gives some advice on how to read technical papers: How To Read Papers

 

General Papers

  1. D. Torrieri, "Statistical Theory of Passive Location Systems," IEEE Transactions on Aerospace and Electronic Systems, pp. 183 - 198, March 1984
  2. W. Gardner, "Likelihood Sensitivity and the Cramer-Rao Bound," IEEE Transactions on Information Theory, p. 491, July 1979
  3. J. Cadzow, "Least Squares, Modeling, and Signal Processing," Digital Signal Processing, pp. 2 - 20, 1994
  4. W. Press et al., "Ch. 15 Modeling of Data", in Numerical Recipes in C, 2nd Edition, Cambridge Press

Application Papers

  1. S. Stein, "Differential Delay/Doppler ML Estimation with Unknown Signals," IEEE Transactions on Signal Processing, pp. 2717 - 2719, August 1993
  2. T. Berger and R. Blahut, "Coherent Estimation of Differential Delay and Differential Doppler," Proceedings of the 1984 Conference on Information Sciences and Systems, Princeton University, pp. 537 - 541, 1984
  3. M. Fowler, “Analysis of Passive Emitter Location using Terrain Data,” IEEE Transactions on Aerospace and Electronic Systems, pp. 495 – 507, April 2001.
  4. K. Becker, "An Efficient Method of Passive Emitter Location," IEEE Transactions on Aerospace and Electronic Systems, pp. 1019 – 1104, Oct. 1992
  5. P. Chestnut, "Emitter Location Accuracy using TDOA and Differential Doppler," IEEE Transactions on Aerospace and Electronic Systems, pp. 214 - 218.
  6. M. Fowler, “Air‑to‑Air Passive Location,” U.S. Patent #5,870,056  Issued 2/9/1999
  7. D. Rife and Boorstyn, "Single-Tone Parameter Estimation from Discrete-Time Observations," IEEE Transactions on Information Theory, pp. 591 - 598, Sept. 1974.
  8.  S. Tretter, "Estimating the Frequency of a Noisy Sinusoid by Linear Regression," IEEE Transactions on Information Theory, pp. 832 - 835, Nov. 1985.
  9.  S. Kay, "A Fast Accurate Single Frequency Estimator," IEEE Transactions on Acoustics, Speech, and Signal Processing , pp. 1987 - 1990, Dec. 1989.

 

 

Assorted Handouts

 

Lecture Notes

Please download, print out, and bring to the relevant class - see Course Schedule above

These notes are complete versions of my class notes.

    - You'll only need to fill in certain spoken information during class you deem important.

    - This will free you up for in-class thinking (come ready to do some!)

 

There also a few "reading notes" that supplement the textbook's coverage... these are now posted on BB.

 

New PDFs of PPT Charts

 

Notes #1a Probability Review      Notes #1b Vectors and Matrices Review  (See Reading Notes on BB)  

 

Notes #2: Ch 1 Intro to Est       Notes #3: Ch 2 MVUE

 

Notes #4: Ch 3 Cramer Rao Bound Pt. A    Notes #5: Ch 3 Cramer Rao Bound Pt. B

 

Notes #6: Ch 3 Cramer Rao Bound Pt. C   Notes #7: Ch 3 Cramer Rao Bound Pt. D

 

Notes #8: Ch 3 CRLB Examples  Notes #9: CRLB Example for Doppler Location (See Reading Notes on BB)

 

Notes #10 Ch_4 Linear Models      Notes #11 Ch_6 BLUE

 

Notes #12 Ch7A    Notes #13 Ch7B    Notes #14 Ch7C   Notes #15 ML Example

 

Notes #16 Ch8A    Notes #17 Ch8B    Notes #18 Ch8C    Notes #19 Ch8D

 

Notes #20 LS Single Platform (See Reading Notes on BB)   Notes #21 Doppler Tracking  (See Reading Notes on BB)

 

Notes #22 Results for 2 RVs (Pre-Ch. 10)  (See Reading Notes on BB)

 

Notes #23 Ch10A    Notes #24 Ch10B (See Reading Notes on BB)

 

Notes #25 Ch11A    Notes #26 Ch11B

 

Notes #27 Ch12A    Notes #28 Ch12B

 

Notes #29 Ch13A    Notes #30 Ch13B

 

Notes #31 Ch13C    Notes #32 Ch13D

Homework Assignments

Project Information

A significant portion of your grade will be based on a project.  It is important to start early

Things you can do early-on are:

  1. Understand the Signal Model and Project Issues
  2. Derive/Analyze Cramer-Rao bounds for your problem
  3. Write simulation code to generate the data

Things you can do by mid-semester are:

  1. Estimator derivation and analysis (most projects will use classical methods, all of which we will have studied by Spring Break)
  2. Coding of estimator
  3. Start your analyses of effects and/or trade-offs

Things you can do by end of semester are:

  1. Complete your analyses of effects and/or trade-offs
  2. Complete your simulations
  3. Analyze your results
  4. Write your report

Here are three files to help you get started. 

Project Files 

MATLAB Handouts & Links

 

Links of Interest

DSP Tutorials and Reference Material

DSP Demos

Some interactive demos of DSP concepts (e.g., filter design)

 

DSP Tutorial

Some basics of DSP theory and implementation.

 

The Scientist and Engineer's Guide to Digital Signal Processing

A freely downloadable DSP Book!!!!  Provides coverage at the level assumed as a pre-requisite for EE522 - so it's a good place to start if you need a refresher.

 

Signals & Systems Demos (Johns Hopkins University)

A neat set of java applets that demonstrate continuous-time & discrete-time signal processing at the level assumed as a pre-requisite for EE522 - so it's a good place to start if you need a refresher.

 

Estimation Oriented Material

Frequency Estimation

An overview of many different ways to estimate frequency.

 

Blind SNR Estimation

Discusses how to estimate the SNR of a signal.

 

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