• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.493-496
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.3
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• pp.177-183
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• 2003

Recently, Ryu et al. proposed a multiple target DOA tracking algorithm, which has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio. In this paper, a measurement fusion method is presented based on ML(Maximum Likelihood), and the new DOA tracking algorithm is proposed by incorporating the presented fusion method into Ryu's algorithm. The proposed algorithm has a better tracking performance than that of Ryu's algorithm, and it sustains the good features of Ryu's algorithm.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.623-626
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• 2001

센서 array 신호처리에서 DOA(direction of arrival)의 추정에 사용되고 있는 root-MUSIC, TLS-ESPRIT 등과 같은 고해상도 스펙트럼 추정 기법들은 과다한 연산량으로 인하여 실시간 구현이 어렵고, 신호들의 DOA가 근접한 경우에서는 추적 성능이 매우 불안정하게 된다. 이러한 문제점에 대한 대안으로 여러 형태의 부공간 추적 개념을 사용하는 수치기법이 제안되어 왔다 [2], [4], [6]. 본 논문에서는 이들 부공간 추정 기법들을 LS-ESPRIT 기법에 접목하여 그 성능을 비교하고, 개선 방안을 제시하였다.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.12-16
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• 2007

In this paper, a new method is proposed for tracking the direction-of-arrival (DOA) of the wideband moving source incident on uniform linear array sensors. DOA is estimated by focusing transformation matrices. To update focusing matrices along with new data snap shots, we use the FAST (Fast Approximate Subspace Tracking) method. Present focusing matrices are constructed by previous signal and its orthogonal basis vectors as well as present signal and its orthogonal basis vectors, which are the left and right singular vectors of the inner product of two approximated matrices. Simulation results are shown to illustrate the performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.189-192
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• 2000

본 논문은 Nonstationary 환경에서 동작하는 소나의 DOA추정의 정확도를 높이기 위하여 가변 망각인자를 도입한 새로운 Extended PASTd (Extended Projection Approximation of Subspace Tracking with deflation) 을 제안하고 기존 알고리즘과 비교함으로써 새로운 알고리즘의 향상된 성능을 보인다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.49-54
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• 1999

In this paper, we propose a new method to estimate the initial DOA of a new appearing source in wideband multisource beamforming and tacking with array sensor position calibration algorithm. By using a beampattern formula for initial DOA detection, the proposed method keeps estimation error within possible tracking range and can be applied to several beamformers with different mainlobe width by adjusting DOA resolution. The simulation results show the performances of source detection and tracking.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.2
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• pp.1-6
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• 2005

Ryu et al. proposed a multiple target DOA tracking algorithm using a linear sensor array. In Ryu's algorithm first, the signal subspace is estimated using sensor output and the angular innovations of targets are extracted from the estimated signal subspace. Next, the DOA's of targets are tracked using the angular innovations as the inputs of Kalman filters. Ryu's algorithm has good features that it has no data association problem and is efficient. However, Ryu's algorithm can't be a lied to an arbitrarily shaped array because it was proposed using linear sensor array. Actually, when the sensor array is used in the various application fields, sensors have a position error. Therefore, the sensor array can be an arbitrarily shaped array. In this paper, we propose a multiple target DOA tracking algorithm applicable to an arbitrarily shaped array, and it sustains the good features of Ryu's algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1E
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• pp.7-13
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• 2001

In this paper we propose a new subspace tracking algorithm based on the PASTd (Projection Approximation Subspace Tracking with deflation). The algorithm is obtained via introducing the variable forgetting factor which adapts itself to the time-varying subspace environments. The tracking capability of the proposed algorithm is demonstrated by computer simulations in an abruptly changing DOA scenario. The estimation results of the variable forgetting factor PASTd(VFF-PASTd) outperform those of the PASTd in the nonstationary case as well as in the stationary case.