Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation

This paper considers the performance limits for joint detection and estimation from a finite set-valued observation that is stochastically related to the state or parameter of interest. Detection refers to inference about the existence of the state, whereas estimation refers to inference about its v...

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Main Authors: Rezaeian, M., Vo, Ba-Ngu
Format: Journal Article
Published: I E E E 2010
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/41587
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author Rezaeian, M.
Vo, Ba-Ngu
author_facet Rezaeian, M.
Vo, Ba-Ngu
author_sort Rezaeian, M.
building Curtin Institutional Repository
collection Online Access
description This paper considers the performance limits for joint detection and estimation from a finite set-valued observation that is stochastically related to the state or parameter of interest. Detection refers to inference about the existence of the state, whereas estimation refers to inference about its value, when detected. Since we need to determine the existence/non-existence of the state as well as its value, the usual notion of Euclidean distance error does not jointly capture detection and estimation error in a meaningful manner. Treating the state as set, which can be either empty or singleton, admits a meaningful distance error for joint detection and estimation. We derive bounds on this distance error for a widely used class of observation models. When existence of the state is a certainty, our bounds coincide with recent results on Cramer-Rao bounds for estimation only problems.
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institution Curtin University Malaysia
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publishDate 2010
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spelling curtin-20.500.11937-415872017-09-13T14:18:23Z Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation Rezaeian, M. Vo, Ba-Ngu joint detection and estimation Cramer–Rao bound random finite sets This paper considers the performance limits for joint detection and estimation from a finite set-valued observation that is stochastically related to the state or parameter of interest. Detection refers to inference about the existence of the state, whereas estimation refers to inference about its value, when detected. Since we need to determine the existence/non-existence of the state as well as its value, the usual notion of Euclidean distance error does not jointly capture detection and estimation error in a meaningful manner. Treating the state as set, which can be either empty or singleton, admits a meaningful distance error for joint detection and estimation. We derive bounds on this distance error for a widely used class of observation models. When existence of the state is a certainty, our bounds coincide with recent results on Cramer-Rao bounds for estimation only problems. 2010 Journal Article http://hdl.handle.net/20.500.11937/41587 10.1109/TSP.2009.2037665 I E E E restricted
spellingShingle joint detection and estimation
Cramer–Rao bound
random finite sets
Rezaeian, M.
Vo, Ba-Ngu
Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation
title Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation
title_full Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation
title_fullStr Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation
title_full_unstemmed Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation
title_short Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation
title_sort error bounds for joint detection and estimation of a single object with random finite set observation
topic joint detection and estimation
Cramer–Rao bound
random finite sets
url http://hdl.handle.net/20.500.11937/41587