TY - JOUR

T1 - A recursive algorithm for tracking DOA's of multiple moving targets by using linear approximations

AU - Kagiwada, Hajime

AU - Ohmori, Hiromitsu

AU - Sano, Akira

PY - 1998

Y1 - 1998

N2 - 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.

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.

KW - Array sensor

KW - Array signal processing

KW - Parameter estimation

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M3 - Article

AN - SCOPUS:0032048199

VL - E81-A

SP - 639

EP - 648

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 4

ER -