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Vorlesungsverzeichnis >> Technische Fakultät (TF) >>
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Radar Signal Processing (RSP)- Dozent/in
- Prof. Dr.-Ing. Gerhard Krieger
- Angaben
- Vorlesung
Präsenz
2 SWS, benoteter Schein, ECTS-Studium, ECTS-Credits: 5, Sprache Englisch
Zeit und Ort: Mi 14:00 - 15:30, Raum n.V.; Bemerkung zu Zeit und Ort: Achtung: Raum 0.144; Cauerstr. 6
- Studienfächer / Studienrichtungen
- WF ICT-MA 1-4
WF EEI-MA-AET ab 1
WF EEI-BA ab 5
WF ASC-MA 1-4
WPF ICT-MA-MPS 1-4
- Voraussetzungen / Organisatorisches
Alle Informationen, Vorlesungs- und Übungsaufzeichnungen/Webinare und Materialien stehen auf StudOn zur Verfügung.
Bitte treten Sie dafür dem StudOn-Kurs „LHFT - Radar Signal Processing" bei.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)
- Empfohlene Literatur
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- ECTS-Informationen:
- Credits: 5
- Zusätzliche Informationen
- Schlagwörter: Radar Signalprocessing Signalverarbeitung
Erwartete Teilnehmerzahl: 20, Maximale Teilnehmerzahl: 40
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2021/2022:
- Radar Signal Processing (RSP)
- Institution: Lehrstuhl für Hochfrequenztechnik
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