Synthetic Aperture Radar (SAR) Data Applications

This book provides an in-depth discussion on the applications of Synthetic Aperture Radar (SAR) with a focus on novel ideas, quantitative methods, and research results. It covers diverse topics such as earth observation, object detection and recognition, change detection, navigation, and interference mitigation, highlighting advanced methods like machine learning and deep learning.

Format: Hardback
Length: 278 pages
Publication date: 19 January 2023
Publisher: Springer International Publishing AG

This meticulously assembled volume offers a comprehensive and cutting-edge exploration of numerous applications of Synthetic Aperture Radar (SAR). By seamlessly integrating interdisciplinary domains, the book presents novel ideas, quantitative methodologies, and groundbreaking research findings, poised to revolutionize computational practices and technologies within both academic and industrial spheres. SAR applications encompass a wide range of diverse and often intricate computational techniques, drawing upon machine learning, estimation, statistical learning, inversion models, and empirical models. The book highlights current and emerging applications of SAR data for earth observation, object detection and recognition, change detection, navigation, and interference mitigation. Special emphasis is placed on cutting-edge methods, with a particular focus on machine learning. Contemporary deep learning models in SAR imagery for object detection and recognition are examined, along with corresponding feature extraction and training schemes. State-of-the-art neural network architectures in SAR-aided navigation are compared and analyzed in depth. Additionally, advanced empirical and machine learning models for retrieving land and ocean information, including wind, wave, soil conditions, and more, are explored. This comprehensive volume serves as a valuable resource for researchers, practitioners, and students interested in advancing the field of SAR and its diverse applications.

Weight: 600g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031212246
Edition number: 1st ed. 2022