ECTS - University of Pisa
L'insegnamento di "Multichannel Signal Processing" ha come obiettivo quello di fornire agli studenti le conoscenze fondamentali relative aiall'elaborazione del segnale multicanale e relative applicazioni in campo radar. Prendendo le mosse dai metodi avanzati di stima spettrale (i metodi di base sono già stati visti nel modulo di Statistical Signal Processing) le lezioni preseguono con una dettagliata analisi delle tecniche più comuni di array processing. Nelle ultime 20 ore di lezione gli studenti vedranno alcune applicazioni di tecniche multicanale a sistemi radar STAP, bistatici passivi e MIMO. Le lezioni teoriche sono sempre complementate da esercitazioni in Matlab.
The course of "Multichannel Signal Processing" aims to provide students with the fundamental knowledge related to multichannel signal processing and related applications in the radar field. Starting from the advanced methods of spectral estimation (the basic methods have already been seen in the Statistical Signal Processing module) the lessons continue with a detailed analysis of the most common techniques of array processing. In the last 20 hours of lessons, students will see some applications of multichannel techniques to STAP, passive bistatic and MIMO radar systems. Theoretical lessons are always complemented by exercises in Matlab.
Piccolo progetto su un argomento del corso ed esame orale su tutti gli argomenti svolti a lezione.
Small project on a topic of the course and oral exam on all the topics covered in class.
Gli studenti acquisiranno conoscenze su stima spettrale, array processing, radar STAP, radar bistatici passivi e radar MIMO.
Students will acquire knowledge on spectral estimation, array processing, STAP radar, passive bistatic radar and MIMO radar.
Piccolo progetto su un argomento del corso ed esame orale su tutti gli argomenti svolti a lezione.
Small project on a topic of the course and oral exam on all the topics covered in class.
Gli studenti acquisiranno conoscenze su stima spettrale, array processing, radar STAP, radar bistatici passivi e radar MIMO.
Students will acquire knowledge on spectral estimation, array processing, STAP radar, passive bistatic radar and MIMO radar.
Piccolo progetto su un argomento del corso ed esame orale su tutti gli argomenti svolti a lezione.
Small project on a topic of the course and oral exam on all the topics covered in class.
Conoscenze di base di teoria della stima, di teoria della decisione radar, e fondamenti di sistemi radar.
Basic knowledge of estimation theory, radar decision theory, and fundamentals of radar systems.
Lezioni frontali.
Attività didattiche:
- frequenza delle lezioni
- partecipazione alle discussioni
- studio individuale
- ricerca bibliografica
Frequenza: consigliata
Metodi di insegnamento:
- lezioni ed esercitazioni
- apprendimento basato sulle attività / apprendimento basato sui problemi / apprendimento basato sull'indagine
Frontal lessons. Educational activities: - attendance of lessons - participation in discussions - individual study - bibliographic research Frequency: recommended Teaching methods: - lessons and exercises - activity based learning / problem based learning / inquiry based learning
1) Stima spettrale avanzata (20 h): Modified periodogram (Bartlett, Welch), Parameter methods for line spectra (MUSIC, ESPRIT), Filter bank methods (Capon)
2) Array processing (20 h): Introduction to radar array processing and the array data modeBel, ampatterns and Classical Beamforming, Beampattern Shading and Null Steering, Adaptive beamforming, Model-Based Beamforming, Broadband Beamforming, Performance assessment: the Array Gain, Implementation of various Array Processing algorithms in MATLAB.
3) Radar STAP (10 h): Introduction to STAP, Geometry, data collection, target signal model, noise model and jamming model, Clutter model and clutter ridge, Fully adaptive STAP, vector tapering, SIRN and Improvement Factor, covariance matrix estimation, Some techniques of partially adaptive , STAPImplementation of STAP algorithms in MATLAB
4) Radar passivi (5 h): Introduction to Passive Radar. History. Passive radar concept. Bistatic geometry, Typical waveforms and ambiguity function, Passive radar detection theory, MATLAB sessions on passive radars.
5) Radar MIMO (5 h): Introduction to MIMO radars. MIMO radars vs phased arrays, MIMO Radars with collocated antennas and widely separated antennas: DoF and virtual antenna array, MIMO radar detection: coherent and incoherent processing, Implementation of MIMO detection algorithms in MATLAB.
1) Advanced spectral estimation (20 h): Modified periodogram (Bartlett, Welch), Parameter methods for line spectra (MUSIC, ESPRIT), Filter bank methods (Capon)
2) Array processing (20 h): Introduction to radar array processing and the array data mode Bel, ampatterns and Classical Beamforming, Beampattern Shading and Null Steering, Adaptive beamforming, Model-Based Beamforming, Broadband Beamforming, Performance assessment: the Array Gain, Implementation of various Array Processing algorithms in MATLAB.
3) Radar STAP (10 h): Introduction to STAP, Geometry, data collection, target signal model, noise model and jamming model, Clutter model and clutter ridge, Fully adaptive STAP, vector tapering, SIRN and Improvement Factor, covariance matrix estimation, Some techniques of partially adaptive, STAPImplementation of STAP algorithms in MATLAB
4) Passive Radar (5 h): Introduction to Passive Radar. History. Passive radar concept. Bistatic geometry, Typical waveforms and ambiguity function, Passive radar detection theory, MATLAB sessions on passive radars.
5) MIMO radar (5 h): Introduction to MIMO radars. MIMO radars vs phased arrays, MIMO Radars with collocated antennas and widely separated antennas: DoF and virtual antenna array, MIMO radar detection: coherent and incoherent processing, Implementation of MIMO detection algorithms in MATLAB.
Materiale fornito dai docenti.
Material provided by the instructors.
Contattare i docenti per discutere i contenuti del corso e il materiale su cui studiare.
Contact the instructors to discuss the course content and the material to study on.
Piccolo progetto su un argomento del corso ed esame orale su tutti gli argomenti svolti a lezione.
Small project on a topic of the course and oral exam on all the topics covered in class.
