• 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.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.1
• /
• pp.32-40
• /
• 2013

In this paper, we propose a multi-channel speech enhancement algorithm using beamforming and direction-of-arrival (DOA)-based masking. The proposed algorithm enhances noisy speech basically by the linearly constrained minimum variance (LCMV) algorithm and then a mel-scale Wiener filter designed using DOA-based masking is applied to remove still remaining noises. To improve the performance, we optimize the learning rate of the adaptive filters in LCMV and the DOA threshold to detect target speech spectrum. As performance indices, the perceptual evaluation of speech quality (PESQ) score and output SNRs are measured. Experimantal results show that the proposed algorithm outperforms the conventional LCMV beamformer by 0.09 in PESQ score and 5.75 dB in output SNR, respectively.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.623-626
• /
• 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 the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.4
• /
• pp.88-94
• /
• 2007

This paper deals with the performance analysis of 3-dimensional array antenna by DOA estimation and beamforming in GPS receiver for performance improvement by interference elimination. The array antenna in GPS receiver can improve the system performance by estimating DOA of arriving signal direction, making the main beam for desired direction and elimate the jammer signal by nulling while keeping the GPS signal direction by spatial filtering. In this paper, we propose five types of 3-dimensional array antenna and analyze the estimation error via MUSIC algorithm which is used for the estimation of DOA of arrived signal and beamforming performance. In analyzing DOA performance, we measure DOA estimation error, while in analyzing beamformig performance, we measure BER. In beamforming performance analyzing, we use various jammer power and the existence of GPS signal and angle spread. By performing through the computer simulation, Curved (B) 7-element antenna in proposed 3-dimensional array antenna exhibits the superior performance in the DOA estimation, estimation error, BER characteristic and angle spread compared to the rest four array antenna types.

• ETRI Journal
• /
• v.26 no.1
• /
• pp.45-47
• /
• 2004

A resolution enhancement method for estimating the direction-of-arrival (DOA) of signals is presented. The proposed method is by virtually expanding a real array into virtual arrays and then averaging the spatial spectrum of the virtual arrays, each of which has a different aperture size. Superior DOA resolutions are shown in comparison with the standard algorithm, MUltiple SIgnal Classification (MUSIC), for incoherent signals incident on a uniform circular array.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.1
• /
• pp.121-131
• /
• 2015

Passive emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. Accurate emitter localization can be expected when utilizing continuous measurable parameters and a appropriate combination of theirs. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to choose a appropriate combination of parameters for a better localization performance. And we propose the passive emitter localization method based on Levenberg-Marquardt algorithm with combined TDOA/FDOA and DOA to achieve better accuracy of emitter localization which is located on the ground and stationary. In addition, we present a method for determining the initial emitter position for LM algorithm's input to avoid the divergence of estimation and local minimum.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.774-783
• /
• 2020

For the issue of subsurface target localization by reverse projection, a new approach of target localization with different distances based on symmetric sub-array multiple-input multiple-output (MIMO) radar is proposed in this paper. By utilizing the particularity of structure of the two symmetric sub-arrays, the received signals are jointly reconstructed to eliminate the distance information from the steering vectors. The distance-independent direction of arrival (DOA) estimates are acquired, and the localizations of subsurface targets with different distances are realized by reverse projection. According to the localization mechanism and application characteristics of the proposed algorithm, the grid zooming method based on spatial segmentation is used to optimize the locaiton efficiency. Simulation results demonstrate the effectiveness of the proposed localization method and optimization scheme.

• Phonetics and Speech Sciences
• /
• v.4 no.3
• /
• pp.103-110
• /
• 2012

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

• ETRI Journal
• /
• v.28 no.6
• /
• pp.761-769
• /
• 2006

In this paper, we address the problem of closely spaced source localization using sensor array processing. In particular, the performance efficiency (measured in terms of the root mean square error) of the unconditional maximum likelihood (UML) algorithm for estimating the direction of arrival (DOA) of near-field sources is evaluated. Four parameters are considered in this evaluation: angular separation among sources, signal-to-noise ratio (SNR), number of snapshots, and number of sources (multiple sources). Simulations are conducted to illustrate the UML performance to compute the DOA of sources in the near-field. Finally, results are also presented that compare the performance of the UML DOA estimator with the existing multiple signal classification approach. The results show the capability of the UML estimator for estimating the DOA when the angular separation is taken into account as a critical parameter. These results are consistent in both low SNR and multiple-source scenarios.