Subject Area | Signals, Communications, and Networking |
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Semester | Semester 9 – Fall |
Type | Elective |
Teaching Hours | 4 |
ECTS | 6 |
Prerequisites |
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Course Director |
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Course Instructor |
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- Review of digital signal processing (DFT, digital filters).
- Basic radar concepts: Introduction to the radar system, fast time, slow time, radar data cube.
- Signal Models: Radar equation, radar cross-section, clutter, frequency models (Doppler shift)
- Matched Filter (MF): MF for ranging, range resolution, MF for moving targets, ambiguity function.
- Radar Waveforms: Rectangular pulse, pulse burst, linear FM, FMCW, bandwidth/Doppler and resolution analysis of waveforms. Radar waveforms for specific applications (automotive, air target monitoring, weather).
- Doppler Processing: Doppler shift in RF signals, Doppler-range response.
- Detection theory: MAP/ML rules, vector detection of deterministic signals, Neyman Parson rule and ROC.
- Antenna Arrays: ULAs, movement and radial velocity models, beamforming and MUSIC algorithm for AoA estimation, Doppler-AoA profile.
- Synthetic aperture radar (SAR) and Imaging.
The course is an undergraduate introduction to radar systems. Emphasis is given in the signal processing aspect of radar systems instead of a theoretical treatment of the subject. The main objectives of the course are two. First, To understand the basic signal processing components/algorithms and their need in any radar system. Second, to be able to adapt these algorithms depending on given radar specifications.
After successfully completing the course the student will be able to:
- Explain the operation a generic radar system and understand a system given to them.
- Evaluate which algorithm should be deployed depending on the specific radar application requirements.
- Fully design and implement in MATLAB/Python the signal processing algorithms of a basic radar system.
The previous learning outcomes will be evaluated based on 5 projects that will train the student in each one of the core components of a radar system. Also through a final exam that requires numerical as well as conceptual solutions to problems.