- Teaching in italian
- RADAR SYSTEMS
- RADAR SYSTEMS
- Subject area
- Reference degree course
- AEROSPACE ENGINEERING
- Course type
- Master's Degree
- Teaching hours
- Frontal Hours: 54.0
- Academic year
- Year taught
- Course year
- CURRICULUM AEROSPACE SYSTEMS
- Reference professor for teaching
- RICCI Giuseppe
Knowledge (at an undergraduate level) of Signal and Systems and Probability Theory is highly desirable
A review of basic concepts from signal theory.
Generalities on radar signal processing (pulsed radars).
The radar equation (with general info on antennas and the radar cross section of a target).
A review from probability theory.
Detection theory and CFAR techniques.
Introduction to Matlab and Monte Carlo simulation.
Analysis (via Monte Carlo simulation) of selected decision schemes.
An introduction to the main concepts of radar systems with emphasis on radar signal processing.
Knowledge and understanding
After the course the student should be able to describe
1.1) the main blocks of a radar system
1.2) signal and interference models
1.3) link budget analysis
1.4) the use of detection theory to design a radar receiver
1.5) CFAR techniques
Applying knowledge and understanding
After the course the student should be able to
2.1) Formulate and solve simple detection problems resorting to the optimum (i.e., Neyman-Pearson test or UMP test) if possible or to a suboptimum one (GLRT).
2.2) Evaluate the performance parameters of a radar system for simplified scenarios by Monte Carlo simulation (Octave/Matlab project).
Students should acquire the ability to compare pros and cons of different approaches to the solution of a specific problem through examples and problems.
The ability to communicate on technical topics should be acquired by discussing the adopted solution to a specific problem with a good balance of mathematical rigor and physical insights.
Selected problems will be proposed that require elaborating on introduced concepts and methods. Identifying solutions to non trivial problems, also with the help of the instructor, will be important to be ready for autonomous lifelong learning.
Lectures, assigned homeworks, solution to proposed problems, and computer projects.
Oral exam. The exam consists of a first part devoted to the discussion of a couple of theoretical topics (this part is aimed at assessing to what extent the student has gained knowledge of topics 1.1-1.5, see Course aims) and a second part focused on the discussion of a Matlab project or the solution of a simple detection problem (this part is aimed at verifying to what extent the student is able to apply knowledge and understanding). Knowledge of topics 1.1-1.5 is necessary to pass the exam together with the ability to discuss a project developed during the course. For scores above 24/30 an in depth knowledge of the mathematical aspects of topics 1.1-1.5 is also required. For scores above 28/30 the ability to solve a simple detection problem is also requested.
Radar Principles by Nadav Levanon, John Wiley & Sons, 1988.
Handouts (in progress).
First Semester (dal 18/09/2023 al 22/12/2023)
Type of assessment
Oral - Final grade