Efficient search strategies for non-myopic sensor scheduling in target tracking

Amit S. Chhetri; Darryl Morrell; Antonia Papandreou-Suppappola

Efficient search strategies for non-myopic sensor scheduling in target tracking

Amit S. Chhetri, Darryl Morrell, Antonia Papandreou-Suppappola

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

19 Scopus citations

Abstract

We propose two tree pruning algorithms to reduce the computational complexity of non-myopic sensor scheduling for target tracking. We consider a mobile bearings-only sensor that chooses from a finite set of possible moves at each time epoch. The scheduling objective is to select the sequence of sensor moves to minimize a tracking cost over M > 1 future time epochs. Tracking is performed with a particle filter, and expected future costs are calculated using an unscented transform with the particle filter. Simulation shows that the two algorithms significantly reduce the time and memory requirements compared to exhaustive search.

Original language	English (US)
Title of host publication	Conference Record - Asilomar Conference on Signals, Systems and Computers
Editors	M.B. Matthews
Pages	2106-2110
Number of pages	5
Volume	2
State	Published - 2004
Event	Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 7 2004 → Nov 10 2004

Other

Other	Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers
Country/Territory	United States
City	Pacific Grove, CA
Period	11/7/04 → 11/10/04

ASJC Scopus subject areas

General Engineering

Cite this

Chhetri, AS, Morrell, D & Papandreou-Suppappola, A 2004, Efficient search strategies for non-myopic sensor scheduling in target tracking. in MB Matthews (ed.), Conference Record - Asilomar Conference on Signals, Systems and Computers. vol. 2, pp. 2106-2110, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United States, 11/7/04.

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abstract = "We propose two tree pruning algorithms to reduce the computational complexity of non-myopic sensor scheduling for target tracking. We consider a mobile bearings-only sensor that chooses from a finite set of possible moves at each time epoch. The scheduling objective is to select the sequence of sensor moves to minimize a tracking cost over M > 1 future time epochs. Tracking is performed with a particle filter, and expected future costs are calculated using an unscented transform with the particle filter. Simulation shows that the two algorithms significantly reduce the time and memory requirements compared to exhaustive search.",

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year = "2004",

language = "English (US)",

volume = "2",

pages = "2106--2110",

editor = "M.B. Matthews",

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AU - Morrell, Darryl

AU - Papandreou-Suppappola, Antonia

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N2 - We propose two tree pruning algorithms to reduce the computational complexity of non-myopic sensor scheduling for target tracking. We consider a mobile bearings-only sensor that chooses from a finite set of possible moves at each time epoch. The scheduling objective is to select the sequence of sensor moves to minimize a tracking cost over M > 1 future time epochs. Tracking is performed with a particle filter, and expected future costs are calculated using an unscented transform with the particle filter. Simulation shows that the two algorithms significantly reduce the time and memory requirements compared to exhaustive search.

AB - We propose two tree pruning algorithms to reduce the computational complexity of non-myopic sensor scheduling for target tracking. We consider a mobile bearings-only sensor that chooses from a finite set of possible moves at each time epoch. The scheduling objective is to select the sequence of sensor moves to minimize a tracking cost over M > 1 future time epochs. Tracking is performed with a particle filter, and expected future costs are calculated using an unscented transform with the particle filter. Simulation shows that the two algorithms significantly reduce the time and memory requirements compared to exhaustive search.

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M3 - Conference contribution

AN - SCOPUS:21644489975

VL - 2

SP - 2106

EP - 2110

BT - Conference Record - Asilomar Conference on Signals, Systems and Computers

A2 - Matthews, M.B.

T2 - Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers

Y2 - 7 November 2004 through 10 November 2004

ER -

Efficient search strategies for non-myopic sensor scheduling in target tracking

Abstract

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ASJC Scopus subject areas

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