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Chengpeng Hao - Advances in Adaptive Radar Detection and Range Estimation

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Book:
Advances in Adaptive Radar Detection and Range Estimation
Author:
Chengpeng Hao / Danilo Orlando / Jun Liu / Chaoran Yin
Publisher:
Springer
Genre:
Books / Computer
Year:
2021
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5 / 5
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Advances in Adaptive Radar Detection and Range Estimation: summary, description and annotation

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This book provides a comprehensive and systematic framework for the design of adaptive architectures, which take advantage of the available a priori information to enhance the detection performance. Moreover, this framework also provides guidelines to develop decision schemes capable of estimating the target position within the range bin. To this end, the readers are driven step-by-step towards those aspects that have to be accounted for at the design stage, starting from the exploitation of system and/or environment information up to the use of target energy leakage (energy spillover), which allows inferring on the target position within the range cell under test.In addition to design issues, this book presents an extensive number of illustrative examples based upon both simulated and real-recorded data. Moreover, the performance analysis is enriched by considerations about the trade-off between performances and computational requirements.Finally, this book could be a valuable resource for PhD students, researchers, professors, and, more generally, engineers working on statistical signal processing and its applications to radar systems.

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Book cover of Advances in Adaptive Radar Detection and Range Estimation

Chengpeng Hao , Danilo Orlando , Jun Liu and Chaoran Yin

Advances in Adaptive Radar Detection and Range Estimation

Logo of the publisher

Chengpeng Hao

Institute of Acoustics, Chinese Academy of Sciences, Beijing, China

Danilo Orlando

University Niccol Cusano, Roma, Italy

Jun Liu

Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China

Chaoran Yin

School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Science, Beijing, China

ISBN 978-981-16-6398-7 e-ISBN 978-981-16-6399-4

https://doi.org/10.1007/978-981-16-6399-4

Jointly published with Science Press, Beijing, China

The print edition is not for sale in China (Mainland). Customers from China (Mainland) please order the print book from: Science Press.

Jointly published with Science Press, Beijing, China

Science Press 2022

This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.

The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.

The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Acronyms and Symbols

In the sequel, we provide the list of acronyms and symbols used throughout this book:

ACE

Adaptive coherence estimator

AMF

Adaptive matched filter

CAF

Complex ambiguity function

CDF

Cumulative distribution function

CFAR

Constant false alarm rate

CLT

Central limit theorem

CNR

The clutter to noise ratio

CPI

Coherent processing interval

CUT

Cell under test

Continuous wave

ECDF

Empirical CDF

False alarm

FIM

Fisher information matrix

GLRT

Generalized likelihood ratio test

Homogeneous environment

ICM

Interference covariance matrix

Intermediate frequency

IID

Independent and identically distributed

Knowledge-aided

LFM

Linear frequency modulated

LHS

Left hand side

LNA

Low-noise amplifier

LPF

Low-pass filter

MAP

Maximum a posteriori

MIT

Massachusetts Institute of Technology

MLE

Maximum likelihood estimate

PDF

Probability density function

PHE

Partially homogeneous environment

PRF

Pulse repetition frequency

PRI

Pulse repetition interval

PSD

Power spectral density

RCS

Radar cross section

RHS

Right hand side

RMS

Root mean square

SAR

Synthetic aperture radar

SCM

Sample covariance matrix

SINR

Signal-to-interference plus noise ratio

UHF

Ultra high frequency

UMP

Uniformly most powerful

VHF

Very high frequency

VSL

Value of significance level

WWII

World war II

Advances in Adaptive Radar Detection and Range Estimation - image 4

Boldface lower-case letters denote vectors

Advances in Adaptive Radar Detection and Range Estimation - image 5

Boldface upper-case letters denote matrices

Complex conjugate operator

The transpose operator

Advances in Adaptive Radar Detection and Range Estimation - image 8

Complex conjugate transpose operator

Advances in Adaptive Radar Detection and Range Estimation - image 9

The gradient operator

Advances in Adaptive Radar Detection and Range Estimation - image 10

The cumulative operator

The product operator

Advances in Adaptive Radar Detection and Range Estimation - image 12

The Moore-Penrose pseudoinverse of a square matrix

Advances in Adaptive Radar Detection and Range Estimation - image 13

The Kronecker product

Advances in Adaptive Radar Detection and Range Estimation - image 14

The set of natural numbers

Advances in Adaptive Radar Detection and Range Estimation - image 15

The set of real numbers

The Euclidean space of -dimensional real matrices or vectors if - photo 16

The Euclidean space of Advances in Adaptive Radar Detection and Range Estimation - image 17 -dimensional real matrices (or vectors if

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