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Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2020/2021
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 055556 - GEOPHYSICAL AND RADAR IMAGING
  • 055554 - RADAR IMAGING
Docente Monti-Guarnieri Andrea Virgilio
Cfu 5.00 Tipo insegnamento Modulo Di Corso Strutturato
Didattica innovativa L'insegnamento prevede  1.0  CFU erogati con Didattica Innovativa come segue:
  • Blended Learning & Flipped Classroom

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - MI (474) TELECOMMUNICATION ENGINEERING - INGEGNERIA DELLE TELECOMUNICAZIONI*AZZZZ055556 - GEOPHYSICAL AND RADAR IMAGING
055552 - RADAR IMAGING
094789 - GEOPHYSICAL IMAGING
Ing Ind - Inf (Mag.)(ord. 270) - MI (476) ELECTRONICS ENGINEERING - INGEGNERIA ELETTRONICA*AZZZZ055552 - RADAR IMAGING

Obiettivi dell'insegnamento

Objective of the course is to provide knowledge of sensing in whole Electro-Magnetic spectrum with particular attention to Radar imaging.

The focus in on systems for imaging from the close range, up to satellite remote sensing. The building blocks of the whole acquisition and processing chain are analyzed, with emphasis on sensors, scanning methods (antenna arrays), data processing and analytics, calibration, quality evaluation, and integration in Geographic Information System.

The physical properties of EM images are discussed with notions form radiometry, speckle, and targets to show potentials and differences between imaging in optics, multi-spectral, infrared, and Radar.

The in-depth analysis of antenna arrays lead to the base of modern high resolution Synthetic Aperture Radars, multi-static and MIMO Radar. Radar image formation, processing and interferometric methods and applications are presented and practiced within project laboratories that are part of the course. Students would be able to understand features like identification of moving target, sensitivity to millimetric deformations, surface roughness and moisture, penetration through dense media, that makes of Radar a unique imaging systems.  

Remote sensing applications like analysis for geo-hazards, infra-structure stability and health monitoring form space, will be experimented by downloading data from image providers and space agencies, or acquiring with radar equipment available for the course, and processes with Matlab or dedicated tools, up to analysis into GIS like QGIS.

A part of the laboratory projects will be address to automotive Radar: where all the elements of the course, sensors, antenna and scanning (virtual and MIMO arrays), efficient and advanced and image formation will be practiced with the cooperation of a leader industry in telecommunication.


Risultati di apprendimento attesi

Dublin Descriptors

Expected learning outcomes

1 - Knowledge and understanding

Students will gain clear understanding about:

  • the physics behind electromagnetic remote sensing technologies
  • sensors principles, with attention to distributed sensors and sensors arrays
  • signal processing methods for the treatment of electromagnetic remote sensing data
  • specific properties of Radar, Lidar, Optical images, and the possible applications

2 - Applying knowledge and understanding

Students will be able to:

  • Design a  Radar and remote sensing  survey
  • Define a data processing flow chart for processing Radar data.
  • Simulate electromagnetic acquisitions and process them using Matlab
  • Get remote sensing data from image providers/space agencies, integrate and process in a GIS

3 - Making judgements

Students will be able to:

  • Identify qualitatively and quantitatively pros and cons of different remote sensing methods and products serving their professional activities
  • Understand the principles that govern the design of Radar remote sensing systems
  • Define a data processing flow chart for processing Radar data.
  • Recognize the design space and its degrees of freedom that can be exploited to define new technologies

4 - Communication

Students will learn to:

  • Write a technical document on a specific case study (e.g.: design and implementation of a remote sensing survey, algorithm development, system analysis, etc.)

5-Lifelong learning skills

 

Students will learn to:

  • Manage a project, starting from definition of specfics, to solution development, validation and verification

Argomenti trattati

Remote sensing principles, methods and applications: from IR to visibleReview of principles: Plank, Wien, Boltzmann laws. Radiance, reflectance & Kirchhoff law. Remote sensing imagers: radiometers, spectrometers, optical satellites. Image generation (acquisition, scanning), properties (resolution, field of view, noise, number of looks), and processing (calibration, geocoding, detection, data analysis and quality evaluation). Applications and use of optical and radiometric images.

Coherent imaging. Review of plane wave, wave propagation, polarimetry. Properties: speckle and its statistical properties, coherence and radiometric resolution. Example: Lidar. Antenna arrays, real and synthetic, grating lobes, processing (beam-forming, back-propagation) and applications: change identification, high resolution location.

RADAR basics: Doppler Radar (identification of moving target), pulsed radars (precise location by ranging), ambiguities, waveforms (chirp), monostatic and bistatic Radars. Radar cross section, thermal noise and the  Radar equation. Imaging radar (SLAR) and Radar scene properties: distributed and point targets, geometric distortions and image generation (back-projection) in Synthetic Aperture Radars

 RADAR systems and applications: Interferometric, tomographic and polarimetric methods and examples. Applications for digital elevation model generation, millimetric deformation estimation (infra-structures and building stability and health), geo-hazard monitoring, classification, vertical profiling of natural media (ice sheets).

Vehicle Radars: MIMO sytems, 3D imaging, advanced methods (focusing super-resolution), pedestrian and anti-collision applications.


Prerequisiti

Introductory courses in signal processing and mathematics.


Modalità di valutazione

Oral exam either based on discussion of the basics of Radar and EM imaging, or a presentation and discussion of a case or a project, that can be eventually done during the course. The presentation can be given in italian or in english.


Bibliografia
Risorsa bibliografica obbligatoriaAndrea Monti-Guarnieri, Electromagnetic Imaging, Anno edizione: 2015 https://www.dropbox.com/s/zdych7eqn59w4er/appunti_EMI.pdf?dl=0
Risorsa bibliografica facoltativaA. Ferretti, A. Monti Guarnieri, C. Prati, F. Rocca, D. Massonnet, InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation, Editore: ESA TM-19

Software utilizzato
Nessun software richiesto

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
32:30
48:45
Esercitazione
5:00
7:30
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
12:30
18:45
Totale 50:00 75:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.7.2 / 1.7.2
Area Servizi ICT
03/07/2022