Table Of ContentNew Methodologies for Understanding
Radar Data
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New Methodologies for Understanding
Radar Data
Edited by
Amit Kumar Mishra and Stefan Brüggenwirth
The Institution of Engineering and Technology
Published by SciTech Publishing, an imprint of The Institution of Engineering and Technology, London, United
Kingdom
The Institution of Engineering and Technology is registered as a Charity in England & Wales (no. 211014) and
Scotland (no. SC038698).
© The Institution of Engineering and Technology 2021
First published 2021
This publication is copyright under the Berne Convention and the Universal Copyright Convention. All rights
reserved. Apart from any fair dealing for the purposes of research or private study, or criticism or review, as
permitted under the Copyright, Designs and Patents Act 1988, this publication may be reproduced, stored or
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Enquiries concerning reproduction outside those terms should be sent to the publisher at the undermentioned
address:
The Institution of Engineering and Technology
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While the author and publisher believe that the information and guidance given in this work are correct, all parties
must rely upon their own skill and judgement when making use of them. Neither the author nor publisher
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The moral rights of the author to be identified as author of this work have been asserted by him in accordance
with the Copyright, Designs and Patents Act 1988.
British Library Cataloguing in Publication Data
A catalogue record for this product is available from the British Library
ISBN 978-1-83953-188-0 (hardback)
ISBN 978-1-83953-189-7 (PDF)
Typeset in India by Exeter Premedia Services Private Limited
Printed in the UK by CPI Group (UK) Ltd, Croydon
Contents
About the editors
1 New methods for radar signal understanding
Stefan Brüggenwirth and Amit Kumar Mishra
1.1 A philosophical introduction
1.2 Automated reasoning
1.3 The role of perception in cognitive radar
1.3.1 Fuster’s model of cognition
1.3.2 Three-layer cognitive radar architecture
1.3.3 DIKW pyramid
1.3.4 Bio-inspired approaches
1.4 A brief history of endeavours to understand signal coming from radar
1.4.1 What is signal understanding?
1.4.2 A brief history
1.5 The scope and a brief outline of this monograph
1.5.1 Brief outline of the book
References
2 Understanding FM radar signal through
parameter estimation
Karol Abratkiewicz and Piotr Jerzy Samczyński
2.1 Problem statement
2.1.1 Radar waveform definition
2.2 Modern methods for analysis of radar signals
2.2.1 Extended generalised chirp transform
2.2.2 Time-frequency methods
2.3 Conclusions
2.4 Summary
References
3 Non-linear estimation algorithms to analyse radar signals
U K Singh, A K Mishra, V Bhatia, and R Mitra
3.1 Introduction
3.2 General radar signal model
3.2.1 Radar signal model in Gaussian noise
3.2.2 LFM radar signal model
3.2.3 OFDM radar signal model
3.2.4 Radar signal model in non-Gaussian clutter
3.2.5 LFM radar signal model in non-Gaussian clutter
3.2.6 SF radar signal model in non-Gaussian clutter
3.3 Batch processing estimation method
3.3.1 Maximum likelihood estimation
3.4 Online non-linear estimator
3.4.1 Reproducing kernel Hilbert space-based estimation
3.4.2 KLMS-based estimators
3.4.3 KMC-based estimators
3.4.4 Kalman filter
3.4.5 EKF- and UKF-based estimation of delay and Doppler shift
Summary
References
4 Understanding radar signals in a highly heterogeneous
clutter environment
Christian Bräu and Fernando Rial
4.1 Introduction
4.2 Understanding resolution limits
4.2.1 Range resolution
4.2.2 Spatial resolution
4.2.3 Dealing with resolution limits in GPR
4.3 Understanding clutter sources
4.3.1 Surface clutter
4.3.2 Subsurface clutter
4.3.3 Dealing with clutter sources in GPR
4.4 Multistatic GPR systems
4.4.1 Example of multistatic systems for clutter reduction
4.5 Full-polarimetric GPR systems
4.5.1 Pauli decomposition
4.5.2 Entropy-α decomposition
4.5.3 Example of full-polarimetric systems for clutter reduction
4.6 Discussion
Acknowledgements
References
5 Signature characteristics and discrimination of small
airborne targets with a staring radar
Mohammed Jahangir, Chris Baker, and Gordon Oswald
5.1 Introduction to staring radar
5.1.1 Historical background
5.2 The physical context for staring radar
5.2.1 Geometry of propagation
5.2.2 Fields and information
5.2.3 Understanding micro-motion characteristics
5.3 Robust drone classification using a staring radar
5.3.1 Staring radar system overview
5.3.2 Classification: a two-stage tree approach
5.3.3 Field trials results
5.4 Conclusions
References
6 SAR coherent change detection
David Blacknell, Daniel Andre, and Andrew Bennett
6.1 Introduction
6.2 Coherent change detection
6.2.1 Single image fundamentals
6.2.2 Repeat pass imaging: interferometry and coherent change detection
6.2.3 CCD image formation
6.2.4 Sensitivity
6.2.5 Validation of sensitivity analysis by simulation
6.2.6 Assessment of detectability of change
6.3 Frequency support fundamentals
6.3.1 Band-limited images
6.3.2 Coherence theory
6.3.3 Base-banding and analysis of frequency support overlap
6.3.4 Frequency trimming
6.3.5 Impact of frequency support considerations on CCD performance
6.3.6 Performance trade-off example
6.4 Advanced frequency support considerations
6.4.1 Topographic base-banding
6.4.2 Spatially- variant frequency trimming
6.5 Experimental results
6.5.1 Radar measurement facility and experimental set-up
6.5.2 Standard CCD processing
6.5.3 CCD processing using spatially variant trimming
6.5.4 Detection of change using spatially variant trimming
6.6 Summary
References
7 Modern GPR target recognition methods
Fabio Giovanneschi, Kumar Vijay Mishra, and Maria Antonia Gonzalez-Huici
7.1 GPR for buried target recognition
7.1.1 Subsurface EM propagation
7.1.2 GPR systems
7.2 GPR signal processing
7.2.1 Classical pre-processing
7.2.2 Modern GPR processing techniques
7.3 GPR measurements for landmine recognition
7.3.1 Deployed system
7.3.2 Test field
7.4 Sparse representation techniques
7.4.1 OMP
7.4.2 Batch-OMP
7.4.3 Basis pursuit denoising, LASSO, and penalized least square
7.4.4 LARS
7.5 Dictionary learning framework and algorithms
7.5.1 K-SVD
7.5.2 LRSDL
7.5.3 ODL
7.5.4 CBWLSU
7.5.5 DOMINODL
7.5.6 Comparison of DL algorithms
7.6 Adaptive statistical DL evaluation
7.6.1 Training set generation
7.6.2 Similarity measure
7.6.3 Statistical metrics
7.6.4 Evaluation results
7.7 Advanced GPR target recognition
