UNIK4361 – Radar - systems and signal processing
Course description
Course content
The course gives an introduction to how a radar functions, and especially to the digital signal processing used in modern systems. The most important processes for the radar’s performance will be covered, including propagation and reflection of electromagnetic radiation, the radar equation, waveforms, array antennas, Doppler processing, detection theory and tracking. Through exercises using modern numerical tools you will gain practical experience with numerical methods for digital signal processing and calculation of radar performance.
Learning outcome
After completing the course you will:
- Know how a radar is built and understand the principles of behavior.
- Have a basic understanding of how radar signals propagate through a medium, and the mechanisms for signal reflection from the target and unwanted reflections (“clutter”).
- Understand the basic principles of signal processing done in a radar.
- Be able to estimate the performance of a radar based on parameters provided, for example at what distance the radar will be able to detect targets of a given size.
- Be able to assess what type of radar is suitable for which task (choice of waveforms, frequency bands, etc..).
- Be able to use numerical tools to calculate radar performance and to simulate the signal processing in a radar.
Admission
Students admitted at UiO must apply for courses in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.
Nordic citizens and applicants residing in the Nordic countries may apply to take this course as a single course student.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.
Prerequisites
Recommended previous knowledge
The course is based on basic mathematics, including calculations with complex numbers, basic Fourier analysis and probability theory. The exercises are based on modern numerical tools (python, matlab, octave, idl or similar), and students with no experience with at least one such tool must expect extra effort here.
Individual courses that provide useful background knowledge, but that is not necessary in order to benefit from the course, is MAT1100 – Calculus, MAT1110 – Calculus and Linear Algebra, MAT-INF1100 – Modelling and Computations, INF1100 – Introduction to programming with scientific applications (continued) og FYS1120 – Electromagnetism.
Overlapping courses
- 10 credits overlap with UNIK9361 – Radar - systems and signal processing (continued)
- 8 credits overlap with UNIK4360 – Radar (continued)
- 8 credits overlap with UNIK9360 – Radar (continued)
Teaching
3 hours teaching each week (2 hours of lectures and 1 hour exercises). The distribution of lectures vs exercises may vary throughout the semester.
A mandatory exercise must be submitted and approved for the students to attend the exam.
Examination
Final, oral exam at the end of the semester (in case of many students, there may be held a written exam).
A mandatory exercise must be submitted and approved for the students to attend the exam.
Grading scale
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
Explanations and appeals
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.