Radar Signal Processing (RSP)5 ECTS
(englische Bezeichnung: Radar Signal Processing)
(Prüfungsordnungsmodul: Wahlmodule aus dem Angebot der FAU)

Lehrveranstaltungen:

• • Radar Signal Processing
    (Vorlesung, 2 SWS, Gerhard Krieger, Di, 13:00 - 14:30, HF-Technik: BZ 6.18; Online-Angebot. Details Absatz *Voraussetzungen / Organisatorisches*)
  • Radar Signal Processing Exercises
    (Übung, 2 SWS, Gerhard Krieger, Di, 14:30 - 16:00, HF-Technik: BZ 6.18; Online-Angebot. Details Absatz *Voraussetzungen / Organisatorisches*)

Empfohlene Voraussetzungen:

Keine formalen Voraussetzungen, aber grundlegende Kenntnisse erforderlich in Signal- und Systemtheorie, Wahrscheinlichkeitstheorie und linearer Algebra. Von Vorteil wären zudem Vorkenntnisse auf einem Teil der folgenden Gebiete: statistische Signalverarbeitung, Hochfrequenztechnik, Radar und/oder nachrichtentechnische Systeme.

Inhalt:

Radar is a key technology for a growing number of sensing tasks that range from the detection, location and tracking of moving objects to high-resolution imaging of surfaces, sub-surfaces and 3-D volumes. While the traditional radar applications focused on aerospace security, weather services and traffic surveillance, radar is now becoming a central contactless sensor technology for the automotive sector, medical diagnostics, gesture control, civil engineering, as well as large scale environmental and climate change monitoring, to name only a few. Associated with the new applications is an increasing demand for advanced signal processing techniques to extract the relevant information from the microwave echoes acquired by single- and multi-aperture radar systems in complex environments. This lecture will give an overview of a variety of one-, two-, and three-dimensional radar signal and image processing algorithms and their application for different sensing tasks. The theoretical derivations are complemented by computer examples and simulations that form an integral part of both the lecture and the exercises. The lecture covers the following topics:

• Introduction (radar principles & applications, signal & noise models, interference, Doppler shift)

• Basics of Signal Processing with Python (Jupyter Notebooks)

• Data Acquisition (I/Q demodulation, complex signal representation, sampling, quantization)

• Range Processing (radar waveforms, pulse compression, ambiguity function, sidelobe reduction)

• Doppler Processing (MTI, clutter suppression, range-Doppler ambiguities, spectral estimation)

• Detection Theory (target models, Neyman-Pearson criterion, CFAR detector, CRBs)

• Multi-Channel Processing (spatial filtering, interference suppression, adaptive beamforming)

• Synthetic Aperture Radar (basics of coherent imaging, SAR data model, time-domain processing)

• SAR Focusing Algorithms (range-Doppler, chirp scaling, motion compensation, autofocus)

• SAR Image Analysis (image statistics, speckle filtering, segmentation, classification)

• Radar Polarimetry (wave representations, scattering models, polarimetric decomposition)

• Interferometry (interferometric processing chain, statistical performance models, applications)

• Tomography (principles of 3-D imaging, tomographic processing, remote sensing applications)

• Space-Time Adaptive Processing (GMTI, optimum processor, pre- & post-Doppler STAP)

• Advanced Topics (bi- & multistatic radar, MIMO radar, compressive sensing)

Lernziele und Kompetenzen:

Verstehen

• understand the basic principles and applications of radar systems

• understand the statistical properties of SAR images and their combinations

• understand current developments associated with bi- and multistatic SAR, MIMO radar, etc.

Anwenden

• implement signal processing algorithms for radar detection and parameter estimation

• use performance metrics for the evaluation of radar systems and signal processing algorithms

• focus coherent radar raw data into high-resolution SAR images

• apply space-time adaptive processing techniques for ground moving target indication

Analysieren

• select and apply spectral processing techniques for clutter and interference suppression

• simulate the performance of radar systems in complex environments

Erschaffen

• combine multiple complex-valued SAR images into higher-level information products

Literatur:

• The handouts distributed at the beginning of each lecture cover the entire material and are fully sufficient for exam preparation.

• The following literature can be consulted if detailed information is needed on individual aspects:
  

  • M. Richards, Fundamentals of Radar Signal Processing, McGraw-Hill, 2nd ed., 2014
    

  • I. Cumming, F. Wong, Digital Processing of Synthetic Aperture Radar Data, Artech House, 2004
    

  • J. Curlander, R. Donough, Synthetic Aperture Radar Systems & Signal Processing, Wiley, 1991
    

  • F. Ulaby, D. Long, Microwave Radar and Radiometric Remote Sensing, Michigan Press, 2014
    

  • C. Oliver, S. Quegan, Understanding Synthetic Aperture Images, Scitech, 2004
    

  • H. Van Trees, Optimum Array Processing, Wiley Interscience, 2002
    

  • J. Guerci, Space-Time Adaptive Processing for Radar, Artech House, 2nd ed., 2015
    

  • R. Hanssen, Radar Interferometry, Kluwer Academic Publishers, 2001
    

  • J. Li, P. Stoica, MIMO Radar Signal Processing, Wiley, 2008

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:

1. Informations- und Kommunikationstechnik (Master of Science)
   (Po-Vers. 2016s | TechFak | Informations- und Kommunikationstechnik (Master of Science) | Gesamtkonto | Wahlbereiche, Praktika, Seminar, Masterarbeit | Wahlmodule aus dem Angebot der FAU)

Studien-/Prüfungsleistungen:

Radar Signal Processing (Prüfungsnummer: 44001)

(englischer Titel: Radar Signal Processing)

Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 30, benotet, 5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

Prüfungssprache: Deutsch oder Englisch

Erstablegung: WS 2020/2021, 1. Wdh.: SS 2021

1. Prüfer:

Gerhard Krieger