Abstract
This book covers the latest developments in radar micro-Doppler signatures and non-cooperative recognition of moving targets, for researchers and advanced students of radar systems. Micro-Doppler signatures is a very broad topic with applications in healthcare, security and surveillance. Edited by leading researchers in the field, the book consists of a series of chapters with contributions from different groups of authors who are international experts on their topics.
The following topics are covered: multistatic radar micro-Doppler; passive radar approaches for healthcare; sparsity-driven methods for micro-Doppler detection and classification; deep neural networks for radar micro-Doppler signature classification; classification of personnel for ground-based surveillance; multimodal sensing for assisted living using radar; micro-Doppler analysis of ballistic targets; small drones and bird signatures as emerging targets; hardware development and applications of portable FMCW radars; digital-IF CW Doppler radar and its contactless healthcare sensing; L1-norm principal component and discriminant analyses of micro-Doppler signatures for indoor human activity recognition; and micro-Doppler signature extraction and analysis for automotive application. Finally, the editors have written a concluding short chapter that brings together an overview of the field and discusses likely future trends.
The following topics are covered: multistatic radar micro-Doppler; passive radar approaches for healthcare; sparsity-driven methods for micro-Doppler detection and classification; deep neural networks for radar micro-Doppler signature classification; classification of personnel for ground-based surveillance; multimodal sensing for assisted living using radar; micro-Doppler analysis of ballistic targets; small drones and bird signatures as emerging targets; hardware development and applications of portable FMCW radars; digital-IF CW Doppler radar and its contactless healthcare sensing; L1-norm principal component and discriminant analyses of micro-Doppler signatures for indoor human activity recognition; and micro-Doppler signature extraction and analysis for automotive application. Finally, the editors have written a concluding short chapter that brings together an overview of the field and discusses likely future trends.
| Original language | English |
|---|---|
| Publisher | The Institute of Engineering and Technology (IET) |
| Number of pages | 424 |
| ISBN (Print) | 978-1-78561-933-5 |
| Publication status | Published - 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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