Temporal fusion in multi-sensor target tracking systems

Ruixin Niu; Pramod Varshney; Kishan Mehrotra; Chilukuri Mohan

doi:10.1109/ICIF.2002.1020925

Temporal fusion in multi-sensor target tracking systems

Ruixin Niu, Pramod Varshney, Kishan Mehrotra, Chilukuri Mohan

Department of Electrical Engineering & Computer Science

Research output: Contribution to conference › Paper › peer-review

7 Scopus citations

Abstract

For a multi-sensor tracking system, the effects of temporally staggered sensors are investigated and compared with synchronous sensors. To make fair comparisons, a new metric, the average estimation error variance, is defined. Many analytical results are derived for sensors with equal measurement noise variance. Temporally staggered sensors always result in a smaller average error variance than synchronous sensors. The corresponding optimal staggering pattern is such that the sensors are uniformly distributed over time. For sensors with different measurement noise variances, the optimal staggering pattern can be found numerically. Intuitive guidelines on selecting optimal staggering pattern have been presented for different target tracking scenarios.

Original language	English (US)
Pages	1030-1037
Number of pages	8
DOIs	https://doi.org/10.1109/ICIF.2002.1020925
State	Published - 2002
Event	5th International Conference on Information Fusion, FUSION 2002 - Annapolis, MD, United States Duration: Jul 8 2002 → Jul 11 2002

Other

Other	5th International Conference on Information Fusion, FUSION 2002
Country/Territory	United States
City	Annapolis, MD
Period	7/8/02 → 7/11/02

Keywords

A-B filter
Asynchronous sensors
Multi-sensor systems
Sensor fusion
Target tracking

ASJC Scopus subject areas

Information Systems

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10.1109/ICIF.2002.1020925

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title = "Temporal fusion in multi-sensor target tracking systems",

abstract = "For a multi-sensor tracking system, the effects of temporally staggered sensors are investigated and compared with synchronous sensors. To make fair comparisons, a new metric, the average estimation error variance, is defined. Many analytical results are derived for sensors with equal measurement noise variance. Temporally staggered sensors always result in a smaller average error variance than synchronous sensors. The corresponding optimal staggering pattern is such that the sensors are uniformly distributed over time. For sensors with different measurement noise variances, the optimal staggering pattern can be found numerically. Intuitive guidelines on selecting optimal staggering pattern have been presented for different target tracking scenarios.",

keywords = "A-B filter, Asynchronous sensors, Multi-sensor systems, Sensor fusion, Target tracking",

author = "Ruixin Niu and Pramod Varshney and Kishan Mehrotra and Chilukuri Mohan",

year = "2002",

doi = "10.1109/ICIF.2002.1020925",

language = "English (US)",

pages = "1030--1037",

note = "5th International Conference on Information Fusion, FUSION 2002 ; Conference date: 08-07-2002 Through 11-07-2002",

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TY - CONF

T1 - Temporal fusion in multi-sensor target tracking systems

AU - Niu, Ruixin

AU - Varshney, Pramod

AU - Mehrotra, Kishan

AU - Mohan, Chilukuri

PY - 2002

Y1 - 2002

N2 - For a multi-sensor tracking system, the effects of temporally staggered sensors are investigated and compared with synchronous sensors. To make fair comparisons, a new metric, the average estimation error variance, is defined. Many analytical results are derived for sensors with equal measurement noise variance. Temporally staggered sensors always result in a smaller average error variance than synchronous sensors. The corresponding optimal staggering pattern is such that the sensors are uniformly distributed over time. For sensors with different measurement noise variances, the optimal staggering pattern can be found numerically. Intuitive guidelines on selecting optimal staggering pattern have been presented for different target tracking scenarios.

AB - For a multi-sensor tracking system, the effects of temporally staggered sensors are investigated and compared with synchronous sensors. To make fair comparisons, a new metric, the average estimation error variance, is defined. Many analytical results are derived for sensors with equal measurement noise variance. Temporally staggered sensors always result in a smaller average error variance than synchronous sensors. The corresponding optimal staggering pattern is such that the sensors are uniformly distributed over time. For sensors with different measurement noise variances, the optimal staggering pattern can be found numerically. Intuitive guidelines on selecting optimal staggering pattern have been presented for different target tracking scenarios.

KW - A-B filter

KW - Asynchronous sensors

KW - Multi-sensor systems

KW - Sensor fusion

KW - Target tracking

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DO - 10.1109/ICIF.2002.1020925

M3 - Paper

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EP - 1037

T2 - 5th International Conference on Information Fusion, FUSION 2002

Y2 - 8 July 2002 through 11 July 2002

ER -

Temporal fusion in multi-sensor target tracking systems

Abstract

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Keywords

ASJC Scopus subject areas

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