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

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.609-612
• /
• 2000

본 논문에서는 음원에 관한 정보가 미지의 상황에서 마이크로폰 어레이를 사용하여 두 음원신호를 분리하는 ,시스템을 제안한다 이 시스템은 두 단계로 구성되어 있으며, 첫 번째 단계에서는 파워가 큰 제 1음원의 DOA(Direction Of Arrival)를 추정하고, AMUSE(Algorithm for Multiple Unknown Signals Extraction)법을 사용한 Blind Deconvolution에 의해 음원신호의 분리를 행한다 두 번째 단계에서는 파워가 낮은 제 2음원의 강조신호를 사용하여 DSA(Delay and Sum Array)법에 의해 제 2음원의 DOA를 추정하고,AMUSE법의 출력신호와 두 음원의 DOA를 이용하여 ANF(Adaptive Notch Filter)를 구성하고, 두 음원신호의 재 분리를 행한다. 그리고, 시뮬레이션을 통해 제안한 방법의 유효성을 검토한 결과 두 음원 신호가 분리 가능한 것이 확인되었다.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.4
• /
• pp.164-173
• /
• 1996

This paper presents an alternative technique for DOA (direction-of-arrival) estimation. For generating a weight vector orthogonal to the signal subspace, a modified version of MES (minimum eigenvalue searching ) method is introduced. The performance of the proposed technique is compared to that of the conventional ED (eigen decomposition) method in terms of angle resolution for a number of snapshots during agiven observation period as well as various SNR's. In addition, the superiority of the suggested technique is shown, by analyzing the required computational load of the proposed MES and conventional ED method. A novel procedure of simplifying the MES proposed in [1] is presented on that purpose. Another advnatage of the proposed technique is that it is performed independently of the detection of the number of signal components, which makes it possible to estimate the DOA's of clusters consisting of infinite number of inseparable signal components.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1788-1789
• /
• 2011

In order to develop a one-axis gimbaled acoustic source tracker for mobile robots, a pseudo-linear direction of arrival(DOA) estimator is proposed using a linear ultrasonic sensor array. Under the assumption that the sensor measurement errors are negligible, a linear measurement model is derived using the linear prediction relation of the received sinusoidal acoustic signals. Applying the Kalman filtering technique for this model, the linear recursive DOA estimator is designed. For its linear recursive filter structure, it is preferable for real-time implementation on a commercial DSP. Through the experiments, the effectiveness of the suggested method is demonstrated.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.06c
• /
• pp.465-468
• /
• 1998

본 논문은 천해 상에서 목표물로부터 방사되어 견인 이동되는 하이드로폰을 통하여 입사되는 광대역 신호에 대한 DOA (Direction-Of Arrival) 추정기법을 제안한다. 견인 배열 어레이를 이용하는 경우 고정된 위치의 배열 하이드로폰을 사용하는 경우와는 달리 움직임에 의한 도플러 주파수 천이 값이 발생하며 배열 상에 입사되는 광대역 신호는 각 주파수성분에 따라 서로 다른 고유 벡터 영역을 갖게 된다. 따라서 주파수 성분별로 처리하여 평균 공간 스펙트럼을 구하여 입사각을 추정하는 기존의 Incoherent 처리기법은 심각한 추정 오차를 발생시킨다. 본 논문에서는 이러한 문제점을 해결하기 위하여 각 주파수 성분에 대한 고유한 벡터영역들을 Coherent 변환과정을 거쳐서 통합된 벡터영역으로 변환하여 공간 스펙트럼을 추정하고 이를 통하여 입사각을 추출한다. 시뮬레이션 결과를 통하여 Cherent 처리기법을 이용한 입사각 추정상의 우수한 성능을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.2
• /
• pp.345-353
• /
• 1994

This paper proposes a high resolution direction finding method, which is so called the 'averaged MUSIC'. This method uses a new sample array covariance matrix that consists of diagonal components obtained by taking averages of the diagonal component values of the sample covariance matrix for the MUSIC. This paper also shows that the proposed method performs higher resolced direction-of-arrival estimation than the MUSIC in such cases as low signal-to-noise ratio, closed signal sources, and limited number of sensors, based on the statistical analysis.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2002.11a
• /
• pp.44-48
• /
• 2002

This paper describes an adaptive signal processing of digital receiver with DDC(Digital Down Convertor), DDC is implemented by using NCO(Numerically Controlled Oscillator), digital low pass filter. for the passband sampling, we present the results of digital receiver simulation with DDC. We confirm that the low IP signal is converted to zero IF by DDC. DOA(Direction Of Arrival) estimation technique using MUSIC(Multiple SIgnal Classification) algorithm with high resolution is presented. We Cow that an accurate resolution of DOA depends on the input sampling number.

• Phonetics and Speech Sciences
• /
• v.3 no.3
• /
• pp.91-98
• /
• 2011

In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.2
• /
• pp.340-346
• /
• 1996

In this paper, we propose a ne weighted backward covariance matrix method to enhance the resolution for direction-of-arrival(DOA) estimation. The proposed method (MEVM:modified eigenvector method) is an enhanced covariance matrix method which is an extended form of the conventional covariance matrix. We analyze the effect of using the weighted forward-baskward covariance matrix on the performance of the eigenvector method(EVM). By comparing the perturbation angle of the noise-subspace, we show that the spectral estimate obtained using the proposed method is less distorted than the spectral estimate obtained using the conventional EVM. The simulation results show that the new method is more accurate and has better resolution than the conventional EVM under the same noise conditions.

• Journal of the Korea Society for Simulation
• /
• v.13 no.2
• /
• pp.1-12
• /
• 2004

This paper estimated the arrival angle and electric wave delay time using the space method law and the directions of arrival (DOA) estimation algorithm in case of signal correlation. Space method law is the method used to repress cross correlation before applying the weight value to the receiving signal. The values of the diagonal elements in the correlation matrix were averaged to replace as the diagonal elements value. In the area of wireless communication or mobile communication, there are high correlations in case of low delay time difference in multiple waves. This causes the quality of the communication to drop due to interference with the desired signal elements. This paper estimated the arrival angle and electric wave delay time using the space method law and the MUSIC algorithm. With the arrival angle algorithm, the arrival angle cannot be estimated below 5 in case of signal correlations because the angle resolution capacity decreases accordingly. The super resolution capacity was estimated to determine the arrival angle below 5 in this paper. In addition, the proposed algorithm estimated the short delay time difference to be below 20ns.