New Methodologies for Understanding Radar Data

Inbunden, Engelska, 2021

Del i serien Radar, Sonar and Navigation

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Beskrivning

Research in the domain of radar signal understanding has seen interesting advances in recent years, mainly due to the developments around cognitive radar and the use of modern machine learning algorithms. This book brings together these strands of research into a coherent and holistic picture, presenting a consolidated approach to understanding radar signals.The book begins with an introduction, which provides some historical and philosophical context to developing methodologies for understanding radar signals, introduces new techniques, and outlines the book's approach to the topic. The book is then divided into three parts: the first focusing on statistical and conventional methods for interpreting radar data; the second addressing compressed sensing and cognitive methods for understanding radar data; and the third covering machine learning methods for understanding radar and remote sensing data.New Methodologies for Understanding Radar Data provides a complete, systematic guide to this multi-faceted topic for advanced researchers and professionals in radar engineering and signal processing.

Produktinformation

Utgivningsdatum:2021-12-23
Mått:160 x 239 x 28 mm
Vikt:976 g
Format:Inbunden
Språk:Engelska
Serie:Radar, Sonar and Navigation
Antal sidor:499
Förlag:Institution of Engineering and Technology
ISBN:9781839531880

Utforska kategorier

Elektronik och kommunikationer inom Naturvetenskap och teknik

Mer om författaren

Amit Kumar Mishra is a professor at the Radar Remote Sensing Group, University of Cape Town, South Africa. Amit has over 15 years of experience in radar and radio system design and signal processing. His current interests are around the use of cognitive architectures and advanced signal processing and machine learning to understand radar signals. He has published more than 35 papers in ISI listed journals and over 120 papers in peer reviewed conference proceedings.Stefan Brüggenwirth is head of the Cognitive Radar Department at the Fraunhofer FHR, Germany and NATO SET panel member-at-large for machine learning and artificial intelligence for RF-systems. Stefan studied aerospace engineering in Stuttgart and Munich, where he did his PhD in the development of a cognitive system architecture for UAV mission management. He spent 2.5 years at NASA Ames Research Center in Mountain View. His research focuses on radar target identification, signal processing architectures and self-learning radar systems.

Innehållsförteckning

Chapter 1: New methods for radar signal understandingChapter 2: Understanding FM radar signal through parameter estimationChapter 3: Non-linear estimation algorithms to analyse radar signalsChapter 4: Understanding radar signals in a highly heterogeneous clutter environmentChapter 5: Signature characteristics and discrimination of small airborne targets with a staring radarChapter 6: SAR coherent change detectionChapter 7: Modern GPR target recognition methodsChapter 8: Jet engine recognition via sparse decomposition of ISAR imagesChapter 9: Waveform design for efficient radar signal recoveryChapter 10: Sea ice concentration estimation techniques using machine learning: an end-to-end workflow for estimating concentration maps from SAR imagesChapter 11: Cognitive radar for ground moving target imagingChapter 12: GAN4SAR: generative adversarial networks for synthetic aperture radar imaging of targets signatureChapter 13: Micro-DopplerChapter 14: Kinematic and linguistic interpretation of human motion via RF signal analysis