DocumentCode
968942
Title
Passive geolocation and tracking of an unknown number of emitters
Author
Sathyan, Thuraiappah ; Sinha, Aloka ; Kirubarajan, Thiagalingam
Author_Institution
Dept. of Electr. & Comput. Eng., McMaster Univ., West Hamilton, Ont., Canada
Volume
42
Issue
2
fYear
2006
fDate
4/1/2006 12:00:00 AM
Firstpage
740
Lastpage
750
Abstract
An algorithm for the geolocation and tracking of an unknown number of ground emitters using the time difference of arrival (TDOA) measurements in practical scenarios is proposed. The focus is on solving the important issue of data association, i.e., deciding from which target, if any, a measurement originated. A previous solution for data association based on the assignment formulation for passive measurement tracking systems relied on solving two assignment problems: an S-dimensional (or SD, where S ≥ 3) assignment for association across sensors and a 2D assignment for the measurement-to-track association. In this paper, (S + 1 )D assignment algorithm - an extension of the SD assignment formulation - that performs the data association in one step, is introduced. It will be shown later that the (S + 1 )D assignment formulation reduces the computational cost significantly without compromising tracking accuracy. The incorporation of correlated measurements, as with the case of TDOA measurements, into the SO framework that typically assumes uncorrelated measurements, is also discussed. The nonlinear TDOA equations are posed as an optimization problem and solved using SolvOpt, a nonlinear optimization solver. The interacting multiple model (IMM) estimator is used in conjunction with the unscented Kalman filter (UKF) to track the geolocated emitters.
Keywords
Kalman filters; position measurement; radio tracking; time-of-arrival estimation; Kalman filter; SolvOpt; data association; ground emitters; interacting multiple model estimator; nonlinear optimization solver; passive geolocation; time difference of arrival measurements; Computational efficiency; Global Positioning System; Intelligent transportation systems; Maximum likelihood estimation; Nonlinear equations; Radar tracking; Sensor systems; Target tracking; Time difference of arrival; Time measurement;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/TAES.2006.1642587
Filename
1642587
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