A Recursive Algorithm for Tracking DOA's of Multiple Moving Targets by Using Linear Approximations

Hajime KAGIWADA; Hiromitsu OHMORI; Akira SANO

A Recursive Algorithm for Tracking DOA's of Multiple Moving Targets by Using Linear Approximations

Hajime KAGIWADA, Hiromitsu OHMORI, Akira SANO

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In this work, a new algorithm for tracking the directions-of-arrival (DOA's) of moving targets by introducing a linear approximation is proposed. The targets are assumed to move with constant angular velocities within a short time and emitting continuously narrow-band signals that impinge on an array of sensors. Therefore the trajectories of targets can be approximated by linear functions of time, which consist of the DOA's and the angular velocities, within the short time. In the condition that the number of targets is known and the outputs vector of the sensors including the additive white complex Gaussian noises is observed continuously, a cost function which consists of the squared residual error vectors is defined. The estimation of the DOA's and the angular velocities of targets is performed by minimizing this cost function. By estimating both the DOA's and the angular velocities at the same time, the proposed algorithm is able to improve the tracking performance for rapidly moving targets. In computer simulations, the performance of the proposed algorithm is compared with the ESPRIT method, which is one of the typical subspace methods with super resolution.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.4 pp.639-648

Publication Date: 1998/04/25

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Category: Digital Signal Processing

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Hajime KAGIWADA, Hiromitsu OHMORI, Akira SANO, "A Recursive Algorithm for Tracking DOA's of Multiple Moving Targets by Using Linear Approximations" in IEICE TRANSACTIONS on Fundamentals, vol. E81-A, no. 4, pp. 639-648, April 1998, doi: .
Abstract: In this work, a new algorithm for tracking the directions-of-arrival (DOA's) of moving targets by introducing a linear approximation is proposed. The targets are assumed to move with constant angular velocities within a short time and emitting continuously narrow-band signals that impinge on an array of sensors. Therefore the trajectories of targets can be approximated by linear functions of time, which consist of the DOA's and the angular velocities, within the short time. In the condition that the number of targets is known and the outputs vector of the sensors including the additive white complex Gaussian noises is observed continuously, a cost function which consists of the squared residual error vectors is defined. The estimation of the DOA's and the angular velocities of targets is performed by minimizing this cost function. By estimating both the DOA's and the angular velocities at the same time, the proposed algorithm is able to improve the tracking performance for rapidly moving targets. In computer simulations, the performance of the proposed algorithm is compared with the ESPRIT method, which is one of the typical subspace methods with super resolution.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_4_639/_p

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@ARTICLE{e81-a_4_639,
author={Hajime KAGIWADA, Hiromitsu OHMORI, Akira SANO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Recursive Algorithm for Tracking DOA's of Multiple Moving Targets by Using Linear Approximations},
year={1998},
volume={E81-A},
number={4},
pages={639-648},
abstract={In this work, a new algorithm for tracking the directions-of-arrival (DOA's) of moving targets by introducing a linear approximation is proposed. The targets are assumed to move with constant angular velocities within a short time and emitting continuously narrow-band signals that impinge on an array of sensors. Therefore the trajectories of targets can be approximated by linear functions of time, which consist of the DOA's and the angular velocities, within the short time. In the condition that the number of targets is known and the outputs vector of the sensors including the additive white complex Gaussian noises is observed continuously, a cost function which consists of the squared residual error vectors is defined. The estimation of the DOA's and the angular velocities of targets is performed by minimizing this cost function. By estimating both the DOA's and the angular velocities at the same time, the proposed algorithm is able to improve the tracking performance for rapidly moving targets. In computer simulations, the performance of the proposed algorithm is compared with the ESPRIT method, which is one of the typical subspace methods with super resolution.},
keywords={},
doi={},
ISSN={},
month={April},}

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TY - JOUR
TI - A Recursive Algorithm for Tracking DOA's of Multiple Moving Targets by Using Linear Approximations
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 639
EP - 648
AU - Hajime KAGIWADA
AU - Hiromitsu OHMORI
AU - Akira SANO
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 1998
AB - In this work, a new algorithm for tracking the directions-of-arrival (DOA's) of moving targets by introducing a linear approximation is proposed. The targets are assumed to move with constant angular velocities within a short time and emitting continuously narrow-band signals that impinge on an array of sensors. Therefore the trajectories of targets can be approximated by linear functions of time, which consist of the DOA's and the angular velocities, within the short time. In the condition that the number of targets is known and the outputs vector of the sensors including the additive white complex Gaussian noises is observed continuously, a cost function which consists of the squared residual error vectors is defined. The estimation of the DOA's and the angular velocities of targets is performed by minimizing this cost function. By estimating both the DOA's and the angular velocities at the same time, the proposed algorithm is able to improve the tracking performance for rapidly moving targets. In computer simulations, the performance of the proposed algorithm is compared with the ESPRIT method, which is one of the typical subspace methods with super resolution.
ER -