[ MEMWFUERASV ] UE Radar Signal Processing
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| Es ist eine neuere Version 2015W dieser LV im Curriculum Master's programme Artificial Intelligence 2021W vorhanden. |
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| (*) Unfortunately this information is not available in english. |
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| Workload |
Education level |
Study areas |
Responsible person |
Hours per week |
Coordinating university |
| 1,25 ECTS |
M2 - Master's programme 2. year |
Mechatronics |
Stefan Schuster |
1 hpw |
Johannes Kepler University Linz |
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| Detailed information |
| Original study plan |
Master's programme Mechatronics 2012W |
| Objectives |
Examples to the course Radar Signal Processing. Programming of Homework in MATLAB. Application of Maximum-Likelihood estimators and derivation of Cramer Rao Bounds.
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| Subject |
- MATLAB
- Radar signal model and Radar cross section
- FFT based frequency estimation
- Random Variables
- Maximum likelihood estimator
- Cramer Rao Bounds
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| Criteria for evaluation |
Homework, oral examination
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| Language |
German, if desired English |
| Study material |
Lecture notes
R. G. Lyons, Understanding Digital Signal Processing, Pearson Education
A. V. Openheim, R. W. Schafer, J. R. Buck, Zeitdiskrete Signalverarbeitung, Pearson Education
S. M. Kay, Intuitive Probability and Random Processes using MATLAB
S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall
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| Changing subject? |
No |
| Corresponding lecture |
(*)ME3WQUENSTE: UE Nachrichtensystemtechnik (1 ECTS)
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| On-site course |
| Maximum number of participants |
35 |
| Assignment procedure |
Assignment according to sequence |
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