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Page 1: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven
Page 2: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven
Page 3: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

What is Detection and Estimation?

Detection: Say whether there is a target or not at the specified cell.

Estimation: Determine range R, velocity v of the target

Page 4: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven
Page 5: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven
Page 6: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven
Page 7: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

Estimation Theory

Level I: Known signals in noise

Level II: Signals with unknown

parameters in noise

Level III: Random signals in noise

Page 8: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

Detection Theory

Level I: Known signals in noise

Level II: Signals with unknown

parameters in noise

Level III: Random signals in noise

Page 9: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

Detection and Estimation

Classical: Hypothesis/parameters are

fixed, non random (deterministic)

Bayesian: Hypothesis/parameters are treated as random variables

wish assumed priors (or a priori distributions)

Application Areas: Radar, Sonar, Speech, Image Analysis,

Biomedicine (medical), communications, control,

seismology, astronomy

Page 10: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven
Page 11: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

Possible approaches for designing good detection and estimation systems using statistical methods:

1. Structured approach

2. Non-structured approach

Estimation Problem: Extract parameter values from a discrete-time waveform or a data set.

Page 12: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

Example-1:

Page 13: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven

Example-2:

Page 14: What is Detection and Estimation?eem.eskisehir.edu.tr/tansufilik/EEM 547/icerik/541_Introduction.pdf · EEM547 Fundamentals of Detection and Estimation Textbooks: 1. 2. 3. Steven