Source Localization: Algorithms and Analysis

H. C. So

doi:10.1002/9781119434610.ch3

Source Localization: Algorithms and Analysis

H. C. So

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 12 - Chapter in an edited book (Author)

Abstract

Time of arrival (TOA), time difference of arrival (TDOA), time sum of arrival (TSOA), received signal strength (RSS), and direction of arrival (DOA) of the emitted signal are commonly used measurements for source localization. This chapter introduces two categories of positioning algorithms based on TOA, TDOA, TSOA, RSS, and DOA measurements. The first category works on the nonlinear equations directly obtained from the nonlinear relationships between the source and measurements. Corresponding examples, namely, nonlinear least squares (NLS) and maximum likelihood (ML) estimators, are presented. The second category attempts to convert the equations to linear. The chapter discusses the linear least squares, weighted linear least squares (WLLS), and subspace approaches. It develops the mean and variance expressions for any positioning method which can be formulated as an unconstrained optimization problem. The Cramer‐Rao lower bound (CRLB), which is a lower bound on the variance attainable by any unbiased location estimator using the same data, is also discussed.

Original language	English
Title of host publication	Handbook of Position Location
Subtitle of host publication	Theory, Practice, and Advances
Editors	S. A. (REZA) ZEKAVAT , R. MICHAEL BUEHRER
Publisher	John Wiley & Sons
Chapter	3
Pages	59-106
Edition	Second
ISBN (Electronic)	978-1-119-43461-0
ISBN (Print)	978-1-119-43458-0
DOIs	https://doi.org/10.1002/9781119434610.ch3
Publication status	Published - 23 Mar 2018

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Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

This research output was also published online on 25 January 2019.

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title = "Source Localization: Algorithms and Analysis",

abstract = "Time of arrival (TOA), time difference of arrival (TDOA), time sum of arrival (TSOA), received signal strength (RSS), and direction of arrival (DOA) of the emitted signal are commonly used measurements for source localization. This chapter introduces two categories of positioning algorithms based on TOA, TDOA, TSOA, RSS, and DOA measurements. The first category works on the nonlinear equations directly obtained from the nonlinear relationships between the source and measurements. Corresponding examples, namely, nonlinear least squares (NLS) and maximum likelihood (ML) estimators, are presented. The second category attempts to convert the equations to linear. The chapter discusses the linear least squares, weighted linear least squares (WLLS), and subspace approaches. It develops the mean and variance expressions for any positioning method which can be formulated as an unconstrained optimization problem. The Cramer‐Rao lower bound (CRLB), which is a lower bound on the variance attainable by any unbiased location estimator using the same data, is also discussed.",

author = "So, \{H. C.\}",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s). This research output was also published online on 25 January 2019.",

year = "2018",

month = mar,

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doi = "10.1002/9781119434610.ch3",

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N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s). This research output was also published online on 25 January 2019.

PY - 2018/3/23

Y1 - 2018/3/23

N2 - Time of arrival (TOA), time difference of arrival (TDOA), time sum of arrival (TSOA), received signal strength (RSS), and direction of arrival (DOA) of the emitted signal are commonly used measurements for source localization. This chapter introduces two categories of positioning algorithms based on TOA, TDOA, TSOA, RSS, and DOA measurements. The first category works on the nonlinear equations directly obtained from the nonlinear relationships between the source and measurements. Corresponding examples, namely, nonlinear least squares (NLS) and maximum likelihood (ML) estimators, are presented. The second category attempts to convert the equations to linear. The chapter discusses the linear least squares, weighted linear least squares (WLLS), and subspace approaches. It develops the mean and variance expressions for any positioning method which can be formulated as an unconstrained optimization problem. The Cramer‐Rao lower bound (CRLB), which is a lower bound on the variance attainable by any unbiased location estimator using the same data, is also discussed.

AB - Time of arrival (TOA), time difference of arrival (TDOA), time sum of arrival (TSOA), received signal strength (RSS), and direction of arrival (DOA) of the emitted signal are commonly used measurements for source localization. This chapter introduces two categories of positioning algorithms based on TOA, TDOA, TSOA, RSS, and DOA measurements. The first category works on the nonlinear equations directly obtained from the nonlinear relationships between the source and measurements. Corresponding examples, namely, nonlinear least squares (NLS) and maximum likelihood (ML) estimators, are presented. The second category attempts to convert the equations to linear. The chapter discusses the linear least squares, weighted linear least squares (WLLS), and subspace approaches. It develops the mean and variance expressions for any positioning method which can be formulated as an unconstrained optimization problem. The Cramer‐Rao lower bound (CRLB), which is a lower bound on the variance attainable by any unbiased location estimator using the same data, is also discussed.

U2 - 10.1002/9781119434610.ch3

DO - 10.1002/9781119434610.ch3

M3 - RGC 12 - Chapter in an edited book (Author)

SN - 978-1-119-43458-0

SP - 59

EP - 106

BT - Handbook of Position Location

A2 - ZEKAVAT , S. A. (REZA)

A2 - BUEHRER, R. MICHAEL

PB - John Wiley & Sons

ER -

Source Localization: Algorithms and Analysis

Abstract

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