B8388 - RADIOLOCALIZZAZIONE E TELERILEVAMENTO AMBIENTALE LM

Learning outcomes

Upon completion of the course, students will: - understand the fundamentals of advanced electromagnetism necessary to understand the interaction of electromagnetic waves with the environment for remote sensing applications; - understand the principles for extracting information about the position and physical characteristics of objects using electromagnetic waves that propagate through and interact with them; - understand the principles, architecture, and operation of the main localization and remote sensing systems and have practical experience with a custom-built radiometer, analyzed during laboratory exercises; - understand examples of the interaction of electromagnetic waves with the environment, including solar radiation, and the application of remote sensing techniques to the monitoring of climate and environmental changes; - understand the main characteristics of Integrated Communication and Sensing (ICAS) techniques.

Course contents

The course focuses on two main topics: radiolocation (positioning) and remote sensing.
Practical exercises and seminars given by expert researchers in the field will be also conducted during the course.

Part 1: RADIOLOCATION
General structure and factors of merit of a radiolocation system. Classification of radiolocation methods: Received Signal Strength (RSS), Time of Arrival (ToA), Time Difference of Arrival (TDoA), Angle of Arrival (AoA). Trilateration and triangulation. Hybrid methods: the example of RADAR. Localization algorithms: measurement errors, impact of real-world propagation on position estimation accuracy; least-squares estimation methods, maximum likelihood methods. Theoretical limits: Cramer-Rao Lower Bound (CRLB) and Geometric Dilution of Precision (GDOP). Localization methods based on radio maps and fingerprinting: Using machine learning techniques for localization via radio maps: the example of the k-Nearest Neighbor (KNN) method. Overview of multipath-assisted techniques; near-field localization techniques and those using reconfigurable intelligent surfaces (RIS). From localization to position tracking: the Kalman filter. Exercises on localization and tracking in a MATLAB/Python environment.

Overview of propagation delay estimation techniques: matched filter, spread spectrum systems with pseudo-noise codes, and a sliding correlator receiver. TDoA estimation via signal cross-correlation. Antenna arrays: estimating the direction of arrival of the radio signal using arrays; overview of super-resolution algorithms (MUSIC, ESPRIT, SAGE).

Main technologies for radio localization.

1. Satellite Technologies: Introduction to the Global Navigation Satellite System (GNSS): GPS, GALILEO, GLONASS, BEIDOU. Operating principles of GPS and other GNSS systems. GNSS system architecture and possible applications: notes on ephemerides and relativistic effects. Introduction to Direct Sequence Spread Spectrum (DSSS) systems. The GPS signal: L1 and L2, C/A and P(Y) codes. GPS receiver operation: acquisition and tracking, DLL and PLL circuits. The GPS navigation message. Overview of the modernized GPS: new L1C, L2C, and L5 signals. Using GNSS for velocity measurements. Using GNSS for time distribution: GPS time vs. UTC vs. TAI time. Main sources of error in GPS: clock offset and drift, ionospheric/tropospheric delay, multipath errors. Differential techniques and common-mode error compensation. Centimeter-precise position estimation using advanced differential GPS techniques: Precise Point Positioning (PPP) and Real-Time Kinematics (RTK). Using GNSS for air navigation: ADS-B and multilateration-based techniques.
2. Radiolocation technologies based on terrestrial radio networks: localization in mobile radio systems from 2G to 5G, characteristics and evolution. High-precision localization using UWB systems (outline). Future 6G systems and the convergence of communication and sensing/localization systems: the Integrated Communication and Sensing (ICAS) paradigm.


PART 2: REMOTE SENSING
Principles and methods for remote sensing. Information acquisition techniques using electromagnetic waves: passive and active remote sensing, cooperative information acquisition. Interaction of electromagnetic radiation with the atmosphere and natural surfaces (vegetation, water, soil). Multispectrality and spectral signatures: examples. Satellite remote sensing: historical overview, basic concepts on the composition of a remote sensing system for Earth observation. Overview of remote sensing applications for: soil (temperature, humidity) and sea surface (water temperature, phytoplankton health), coastal erosion, and support for precision agriculture and viticulture.

Main radiometric quantities: power spectral density, irradiance, radiance, brightness. Overview of corresponding photometric quantities. Electromagnetic emission from bodies: blackbody, graybody, emissivity, and brightness temperature. Interaction between electromagnetic waves, obstacles, and the atmosphere: reflection, absorption, and scattering from rough surfaces; types of scattering in the atmosphere (Rayleigh, Mie, nonselective, Raman).

Fundamentals of passive remote sensing: the microwave radiometer. Optical radiometers and thermal imaging cameras. Overview of some types of electromagnetic sensors at infrared and visible frequencies: quantum sensors (photodiodes and phototransistors), thermopile and bolometric sensors; MOS and charge-coupled detectors (CCD) imaging sensors.

Fundamentals of active remote sensing. Problems of direct and inverse electromagnetic scattering, derivation of the bistatic and monostatic RADAR equation. Monostatic and bistatic RCS, characteristics and their relationship to target characteristics, and an overview of RCS calculation methods (physical optics, electromagnetic ray models). An overview of stealth technology.

Main radar architectures: pulsed radar, incoherent, quasi-coherent, and current reception schemes. Recall of detection and false alarm probabilities, optimal threshold selection, ROC curves. Effects of target RCS fluctuations: Swerling models I, II, III, and IV. Effect of cluttering and equalization methods: Constant False Alarm Rate (CFAR) detection. Radar system design criteria. Advanced transmission techniques: pulse-Doppler radar, pulse compression radar (with Barker codes and chirp waveforms). The Doppler dilemma. Continuous wave (CW) radar, frequency-modulated continuous wave (FMCW) radar. Examples: radar altimeter, vehicle-mounted collision avoidance radar. Main types of radar antennas: conical beam antennas, fan-beam antennas (e.g., cosecant antennas), phased array antennas (e.g., Cobra Dane).

Surveying of land and sea surfaces: radar scatterometers. Radars for high-resolution imaging applications on airborne and satellite platforms: Side-Looking Real Aperture Radar (SLR), Synthetic Aperture Radar (SAR), Differential SAR Interferometry (InSAR). Distortion effects in SAR images: slant-range distortion, layover, shadowing, speckles.

Acquisition and interpretation of remotely sensed images. Radiometric calibration, conversion from digital numbers to radiance and physical parameters. Overview of atmospheric correction and noise filtering techniques. Application of AI techniques to image segmentation and classification: supervised classification methods (minimum mean, maximum likelihood, support vector machine, random forest). Unsupervised classification methods (clustering, k-means, isodata). Matlab/Python exercise on hyperspectral image classification.

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If time remains, one of the following topics will be explored, based on students' interests and preferences:

1) Weather radar: its use for nowcasting, hydrometeor detection (rain, snow, hail), and disaster prevention (floods, hurricanes, inundations, landslides).

2) Solar radiation: solar constant, scattering, and absorption in the atmosphere. Insolation, brightness index, surface reflectivity (albedo), thermal absorption and reemission. Effect of vegetation, CO2 sequestration, and evapotranspiration. Energy balance of an urban area. Impact of global warming and climate change monitoring: an overview of "heat island" effects in urban environments.

3) Active optical remote sensing systems: LIDAR and laser scanners, their use for the detection of pollutants in the atmosphere and measurement of greenhouse gases.

4) Human gesture detection and/or vital signs monitoring using RADAR systems. Application of machine learning techniques for human gesture classification.

Readings/Bibliography

The teacher will provide lesson notes and powerpoint slides. All the teaching materials will be made available on the Moodle/VIRTUALE platform.

Recommended textbooks:

• Brivio P.A., Lechi G., Zilioli E.: Principi e metodi di telerilevamento. Citta' Studi Edizioni, 2006.
• W. G. Rees, "Physical Principles of Remote Sensing", 3rd Edition, Cambridge University Press, 2012.
• F. T. Ulaby, D. G. Long, "Microwave Radar and Radiometric Remote Sensing", Artech House, 2015.
• R. M. Rauber, S. W. Nesbitt, "Radar Meteorology - A first course" Wiley, 2018.
• P. Misra, P. Enge, “Global Positioning System: Signals, Measurements, and Performance (Revised Second Edition)”, Ganga-Jamuna Press, 2012.

Further texbooks for consultation and study in depth of specific topics:

• G. Falciasecca, "Dopo Marconi il diluvio. Evoluzione nell'infosfera", Ed. Pendragon, 2016.
• Merrill Skolnik, "Radar Handbook", Third Edition, McGraw-Hill, 2008.
• F. Berizzi, "I sistemi di telerilevamento Radar", Apogeo, 2010.
  
• C. Elachi, J. Van Zyl, "Introduction to the physics and techniques of Remote Sensing", 2nd Edition, Wiley, 2006.
  
• Kuo-Nan Liou, "An Introduction to Atmospheric Radiation", Academic Press, 1980.
• P. Dong, Q. Chen, "LiDAR Remote Sensing and Applications", CRC Press, 2018
• Claus Weitkamp, "LIDAR : range-resolved optical remote sensing of the atmosphere", Springer, 2005.
• Vosselman G., Maas H.: Airborne and Terrestrial Laser Scanning, Whittles ed., 2010.
• A.I. Kozlov, L.P. Ligthart, A.I. Logvin, "Mathematical and physical modelling of microwave scattering and polarimetric remote sensing", Kluwer Academic Publishers, 2004.
  
• B. Hofmann-Wellenhof, H. Lichtenegger E. Wasle, "GNSS – Global Navigation Satellite Systems. GPS, GLONASS, Galileo, and more", Springer, 2007.
• P. D. Groves, "Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems", Artech House, 2008.
• S. Frattasi, F. Della Rosa, "Mobile Positioning and Tracking - From Conventional to Cooperative Techniques" 2nd Edition, Wiley, 2017.
• D. Dardari, E. Falletti, M. Luise, "Satellite and Terrestrial Radio Positioning Techniques: A Signal Processing Perspective", Academic Press, 2012.

Teaching methods

The course includes lectures and exercises in the classroom and at home.
Application examples will be presented during the lectures, along with numerical exercises similar to those required for the exam.

Periodically, some lectures will be interactive, presenting questions to which students must respond based on the material covered so far.

During the course, some exercises will be conducted in the MATLAB environment. Additionally, a practical demonstration of microwave radiometry and optical frequency sensing will be carried out, and a seminar on an advanced topic will be offered to the students.

Assessment methods

The final assessment consists in an oral examination divided into 3 questions, the first of which must be answered by the candidate in written form. The questions relate to the overall course program.

The first question (written) is aimed at solving a project / numerical problem and normally must be carried out in a maximum time of one hour. The solution of the problem by the candidate is briefly discussed in the oral interview with the teacher who communicates the general evaluation to the student, before proceeding with the 2 following oral questions.

The final marks derive from the overall (average) evaluation of the answers to the 3 questions. Honors are given at the discretion of the teacher if the candidate answers all 3 questions correctly and without significant errors or inaccuracies, and also in the interview demonstrates an excellent capacity for critical analysis and an excellent ability to express the topics covered.

To be able to take the exam it is mandatory to register on ALMAEsami.

Criteria for the assigmnent of the final marks:

Poor knowledge of the topics of the course, inadequate capacity for critical analysis and analysis / solution of practical problems; incorrect or inappropriate expression will result in a negative evaluation. In case of insufficient marks, students will have to repeat the test.

Preparation on a very limited number of topics covered in the course and analytical skills that emerge only with the help of the teacher, expressed in an overall correct language → 18-19;

Preparation on a limited number of topics covered in the course and ability to autonomous analysis only on purely executive matters, expression in correct language → 20-24;

Preparation on a large number of topics covered in the course, ability to make autonomous choices of critical analysis, mastery of specific terminology → 25-29;

Excellent ability to critically analyze the topics covered and excellent ability to express and argue; excellent competence and ability to apply knowledge to practical problems independently → 30-30L.

Students with learning disabilities (DSA) or temporary or permanent disabilities: please contact the relevant University office promptly (https://site.unibo.it/studenti-con-disabilita-e-dsa/it ). The office will be responsible for suggesting any accommodations to the students. These accommodations must be submitted to the instructor for approval 15 days in advance, who will evaluate their suitability also in relation to the educational objectives of the course.

Teaching tools

Slides of lessons, lecture notes, blackboard and projector / camera.

Office hours

See the website of Enrico Maria Vitucci