3. 강의목표
This course focuses on the problem of determining the spectral distribution of a time series (random process) from a finite set of measurements. Spectral estimation techniques can applied to various sensors: active and passive radar in addition to sonar. They can be used in localization of targets, imaging and its interpretation, and direction of arrival (DOA) estimation, etc. Students should learn various spectral estimation paradigms such as nonparametric methods based on FFT, parametric methods for rational (continuous) spectra, parametric methods for line (discrete) spectra, and filter bank methods. Special emphases will be paid upon the application of spectral estimation methods to various kinds of radar signal processing.
4. 강의선수/수강필수사항
Signals and Systems, Discrete-Time Signal Processing (DSP), Random Process, Linear Algebra
5. 성적평가
Mid-Exam(30%), Homeworks(30%), Term Project(40%)
Note: There will be no points for copied homeworks.
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Introduction to Spectral Analysis
|
Petre Stoica and Randolph Moses
|
Prentice-Hall Inc
|
1997
|
|
7. 참고문헌 및 자료
1) Statistical and Adaptive Signal Processing, Dimitris G. Manolakis, Vinay K. Ingle, and Stephen
M. Kogon, McGraw Hill 2000
2) Digital spectral analysis with applications, S. L. Marple Jr., Prentice Hall, 1987
3)Modern spectral estimation, S. M. Kay, Prentice Hall, 1988
8. 강의진도계획
· Random Process and Fourier Transform - Review
· Basic Concepts
· Nonparametric methods
· Mid-Term Exam
· Parametric methods for rational spectra
· Parametric methods for line spectra
· Filter bank methods
· Term Project Presentation
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청